Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
NeurIPS 2024 | August 2024
Aditya Nori
Partner Research Manager
Publications
Publications by Year
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Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
CHI 2024 | May 2024
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
2405.05299 | May 2024
Published by arXiv
Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
Nature Communications | March 2024, Vol 15
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RadEdit: stress-testing biomedical vision models via diffusion image editing
Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
December 2023
Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety
Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Kegan, Usman Munir, Ryutaro Tanno, Hannah Richardson (nee Murfet), Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
PLOS ONE | November 2023, Vol 18(11)
Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
EMNLP 2023 | October 2023
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward
Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
CHI 2023 | April 2023
Compositional Zero-Shot Domain Transfer with Text-to-Text Models
Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie Hyland
TACL 2023 | March 2023
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Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
The European Conference on Computer Vision (ECCV) | October 2022
Repairing Neural Networks by Leaving the Right Past Behind
Ryutaro Tanno, Melanie Fernandez Pradier, Aditya Nori, Yingzhen Li
2022 Neural Information Processing Systems | July 2022
Active label cleaning for improved dataset quality under resource constraints
Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Nature Communications | March 2022, Vol 13(1161): pp. 1-11
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Artificial intelligence in healthcare: transforming the practice of medicine
Junaid Bajwa, Aditya Nori, Bryan Williams, Usman Munir
Future Healthcare Journal | July 2021
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
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Secure Medical Image Analysis with CrypTFlow
Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
NeurIPS PPML Workshop | December 2020
Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
JAMA | November 2020
Towards Compliant Data Management Systems for Healthcare ML
Goutham Ramakrishnan, Aditya Nori, Hannah Richardson (nee Murfet), Pashmina Cameron
November 2020
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
JAMA Network | June 2020, Vol 3(7)
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Overfitting in Synthesis: Theory and Practice
Saswat Padhi, Todd Millstein, Aditya Nori, Rahul Sharma
Computer Aided Verification (CAV) | July 2019
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Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot
Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002
Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot
Physics in Medicine & Biology | November 2018, Vol 63(23)
Autofocus Layer for Semantic Segmentation
Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori
International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018
Semi-Supervised Learning via Compact Latent Space Clustering
Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori
International Conference on Machine Learning (ICML) | June 2018
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FairSquare: Probabilistic Verification for Program Fairness
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
OOPSLA '17: OO Programming, Systems, Languages, and Applications | October 2017
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
Information Processing in Medical Imaging (IPMI) | June 2017
Spectral Kernels for Probabilistic Analysis and Clustering of Shapes
Loic Le Folgoc, Aditya Nori, Antonio Criminisi
Information Processing in Medical Imaging (IPMI) | June 2017
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Fairness as a Program Property
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
Fairness, Accountability, and Transparency in Machine Learning (FATML) | November 2016
DeepMedic for Brain Tumor Segmentation
Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
MICCAI Brain Lesion Workshop | October 2016
Lifted Auto-Context Forests for Brain Tumour Segmentation
Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi
MICCAI Brain Lesion Workshop | October 2016
Measuring Neural Net Robustness with Constraints
Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi
Neural Information Processing Systems (NIPS) | May 2016
Debugging Machine Learning Tasks
Aleksandar Chakarov, Aditya Nori, Sriram Rajamani, Shayak Sen, Deepak Vijaykeerthy
MSR-TR-2016-1135 | March 2016
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A Provably Correct Sampler for Probabilistic Programs
Chung-Kil Hur, Aditya Nori, Sriram Rajamani
Foundations of Software Technology and Theoretical Computer Science (FSTTCS) | December 2015
Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances
Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
SAT '15: International Conference on Theory and Applications of Satisfiability Testing | September 2015
A User-Guided Approach to Program Analysis
Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
Foundations of Software Engineering (FSE) | August 2015
Foundations of Software Engineering (FSE) - ACM SIGSOFT Distinguished Paper
ACM SIGSOFT Distinguished Paper
Learning Refinement Types
He Zhu, Aditya Nori, Suresh Jagannathan
International Conference on Functional Programming (ICFP) | August 2015
International Conference on Functional Programming (ICFP)
Efficient Synthesis of Probabilistic Programs
Aditya Nori, Sherjil Ozair, Sriram Rajamani, Deepak Vijaykeerthy,
Programming Language Design and Implementation (PLDI) | June 2015
Dependent Array Type Inference from Tests
He Zhu, Aditya Nori, Suresh Jagannathan
VMCAI '15: Verification, Model Checking and Abstract Interpretation | January 2015
Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources
Venkatesh Vinayakarao, Rahul Purandare, Aditya Nori
Partial Evaluation and Program Manipulation (PEPM) | January 2015
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R2: An Efficient MCMC Sampler for Probabilistic Programs
Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
AAAI Conference on Artificial Intelligence (AAAI) | July 2014
Slicing Probabilistic Programs
Chung-Kil Hur, Aditya Nori, Sriram Rajamani, Selva Samuel
Programming Language Design and Implementation (PLDI) | June 2014
MUX: Algorithm Selection for Software Model Checkers
Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya Nori
Mining Software Repositories (MSR) | May 2014
Probabilistic Programming
Andy Gordon, Thomas A. Henzinger, Aditya Nori, Sriram Rajamani
International Conference on Software Engineering (ICSE Future of Software Engineering) | May 2014
Bias-Variance Tradeoffs in Program Analysis
Alex Aiken, Aditya Nori, Rahul Sharma
Principles of Programming Languages (POPL) | January 2014
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A Colorful Approach to Text Processing by Example
Kuat Yessenov, Shubham Tulsiani, Aditya Menon, Robert C. Miller, Sumit Gulwani, Butler Lampson, Adam Tauman Kalai
UIST '13 Proceedings of the 26th annual ACM symposium on User interface software and technology | October 2013
Semantics Sensitive Sampling for Probabilistic Programs
Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
MSR-TR-2013-109 | October 2013
Bayesian Inference Using Data Flow Analysis
Guillaume Claret, Sriram Rajamani, Aditya Nori, Andy Gordon, Johannes Borgström
ESEC/FSE 2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering | August 2013
Termination Proofs from Tests
Aditya Nori, Rahul Sharma
Foundations of Software Engineering (FSE) | August 2013
Combining Relational Learning with SMT Solvers using CEGAR
Arun Chaganty, Akash Lal, Aditya Nori, Sriram Rajamani
Computer Aided Verification (CAV) | July 2013
One-bit Compressed Sensing: Provable Support and Vector Recovery
Sivakant Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
International Conference on Machine Learning (ICML) | June 2013
International Conference on Machine Learning (ICML)
Verification as Learning Geometric Concepts
, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya Nori
Static Analysis Symposium (SAS) | June 2013
Static Analysis Symposium (SAS)
Efficiently Sampling Probabilistic Programs via Program Analysis
Arun T. Chaganty, Aditya Nori, Sriram Rajamani
Artificial Intelligence and Statistics (AISTATS) | April 2013
A Data Driven Approach for Algebraic Loop Invariants
, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya Nori
European Symposium on Programming (ESOP) | March 2013
A Model-Learner Pattern for Bayesian Reasoning
Andrew D. Gordon, Mihhail Aizatulin, Guillaume Claret, Thore Graepel, Aditya Nori, Sriram Rajamani, Claudio Russo, Johannes Borgstroem, Andy Gordon
MSR-TR-2013-1 | January 2013
Published by Microsoft
Probabilistic Inference Using Program Analysis
Andy Gordon, Aditya Nori, Sriram Rajamani
January 2013
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Interpolants as Classifiers
Aditya Nori, Alex Aiken
Computer Aided Verification | July 2012
Computer Aided Verification
Parallelizing Top-Down Interprocedural Analyses
Aws Albarghouthi, Rahul Kumar, Aditya Nori, Sriram Rajamani
Programming Languages Design and Implementation (PLDI) | June 2012
Interpolants as Classifiers
Rahul Sharma, Aditya Nori, Alex Aiken,
MSR-TR-2012-13 | January 2012
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Bottom-up shape analysis using LISF
Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori, G. Ramalingam
November 2011
Probabilistic, Modular and Scalable Inference of Typestate Specifications
Nels E. Beckman, Aditya Nori
PLDI '11: Programming Languages Design and Implementation | June 2011
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Alternation for Termination
William R. Harris, Akash Lal, Aditya Nori, Sriram Rajamani
SAS '10: Static Analysis Symposium | September 2010
An Empirical Study of Optimizations in Yogi
International Conference on Software Engineering (ICSE) | May 2010
Proofs from Tests
Nels E. Beckman, Aditya Nori, Sriram Rajamani, Robert J. Simmons, Sai Deep Tetali, Aditya V. Thakur
IEEE Transactions on Software Engineering (special issue on the ISSTA 2008 best papers) | March 2010
ISSTA 2008 best papers
Compositional May-Must Program Analysis: Unleashing the Power of Alternation
Patrice Godefroid, Aditya Nori, Sriram Rajamani, Sai Deep Tetali
Principles of Programming Languages (POPL) | January 2010
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Bottom-up Shape Analysis
Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori
SAS '09: Static Analysis Symposium | August 2009
Measuring the Loss of Privacy from Statistics
Michael C. Tschantz, Aditya Nori
Workshop on Quantitative Analysis of Software | June 2009
Merlin: Specification Inference for Explicit Information Flow Problems
Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
Holmes: Effective Statistical Debugging via Efficient Path Profiling
Trishul Chilimbi, Ben Liblit, Krishna Mehra, Aditya Nori, Kapil Vaswani
Proceedings of the International Conference on Software Engineering (ICSE) | May 2009
The Yogi Project: Software Property Checking via Static Analysis and Testing
Aditya Nori, Sriram Rajamani, Sai Deep Tetali, Aditya V. Thakur,
TACAS '09: Tools and Algorithms for the Construction and Analysis of Systems | March 2009
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Automated Software Testing Using Program Analysis
Patrice Godefroid, Peli de Halleux, Aditya Nori, Sriram Rajamani, Wolfram Schulte, Nikolai Tillmann, Michael Y. Levin
IEEE Software, Special Issue on Software Development Tools | October 2008
Automatically Refining Abstract Interpretations
Bhargav Gulavani, Supratik Chakraborty, Aditya Nori, Sriram Rajamani
Proceedings of the 14th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) | March 2008
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Quantifying the Effectiveness of Testing via Efficient Residual Path Profiling
Trishul Chilimbi, Aditya Nori, Kapil Vaswani
Proceedings of the Symposium on Foundations of Software Engineering (FSE) | September 2007
Preferential Path Profiling: Compactly Numbering Interesting Paths
Kapil Vaswani, Aditya Nori, Trishul Chilimbi
Proceedings of the Symposium on Principles of Programming Languages (POPL) | January 2007
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Unifying Views of Tail-Biting Constructions for Linear Block Codes
Aditya Nori, Priti Shankar
IEEE Transactions on Information Theory | October 2006
SYNERGY : A New Algorithm for Property Checking
Bhargav Gulavani, Thomas Henzinger, Yamini Kannan, Aditya Nori, Sriram Rajamani
MSR-TR-2006-76 | April 2006
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Exact And Approximate Algorithms for ML Decoding on Tail-Biting Trellises
Priti Shankar, Madhu A. S, Aditya Nori
March 2005
Unifying Views of Tail-Biting Trellises for Linear Block Codes
January 2005
January 2005
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A Coset Construction for Tail-Biting Trellises
Aditya Nori, Priti Shankar
Proceedings of the International Symposium on Information Theory and its Applications (ISITA) | October 2004
Proceedings of the International Symposium on Information Theory and its Applications (ISITA)
Decoding Codes on Graphs: Probabilistic Decoding
Madhu A. S, Aditya Nori
Resonance: Journal of Science Education, Indian Academy of Sciences | February 2004
Resonance: Journal of Science Education, Indian Academy of Sciences
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Tail-Biting Trellises for Linear Codes and their Duals
Aditya Nori, Priti Shankar
Proceedings of the Forty-First Annual Allerton Conference on Communication, Control and Computing (Allerton) | October 2003
Decoding Codes on Graphs: Low Density Parity Check Codes
Resonance: Journal of Science Education, Indian Academy of Sciences | September 2003
A BCJR-like Labeling Algorithm for Tail-Biting Trellises
Aditya Nori, Priti Shankar
Proceedings of the IEEE International Symposium on Information Theory (ISIT) | July 2003
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A Technique for Model-Based Testing of Classes
Aditya Nori, Ashok Sreenivas
Proceedings of the Second International Workshop on Software Engineering Tools and Techniques | January 2001
Publications by Research Area
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Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
NeurIPS 2024 | August 2024
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
CHI 2024 | May 2024
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
2405.05299 | May 2024
Published by arXiv
Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
Nature Communications | March 2024, Vol 15
RadEdit: stress-testing biomedical vision models via diffusion image editing
Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
December 2023
Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety
Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Kegan, Usman Munir, Ryutaro Tanno, Hannah Richardson (nee Murfet), Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
PLOS ONE | November 2023, Vol 18(11)
Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
EMNLP 2023 | October 2023
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward
Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
CHI 2023 | April 2023
Compositional Zero-Shot Domain Transfer with Text-to-Text Models
Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie Hyland
TACL 2023 | March 2023
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
The European Conference on Computer Vision (ECCV) | October 2022
Repairing Neural Networks by Leaving the Right Past Behind
Ryutaro Tanno, Melanie Fernandez Pradier, Aditya Nori, Yingzhen Li
2022 Neural Information Processing Systems | July 2022
Active label cleaning for improved dataset quality under resource constraints
Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Nature Communications | March 2022, Vol 13(1161): pp. 1-11
Artificial intelligence in healthcare: transforming the practice of medicine
Junaid Bajwa, Aditya Nori, Bryan Williams, Usman Munir
Future Healthcare Journal | July 2021
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
Secure Medical Image Analysis with CrypTFlow
Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
NeurIPS PPML Workshop | December 2020
Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
JAMA | November 2020
Towards Compliant Data Management Systems for Healthcare ML
Goutham Ramakrishnan, Aditya Nori, Hannah Richardson (nee Murfet), Pashmina Cameron
November 2020
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
JAMA Network | June 2020, Vol 3(7)
Overfitting in Synthesis: Theory and Practice
Saswat Padhi, Todd Millstein, Aditya Nori, Rahul Sharma
Computer Aided Verification (CAV) | July 2019
Autofocus Layer for Semantic Segmentation
Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori
International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018
Semi-Supervised Learning via Compact Latent Space Clustering
Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori
International Conference on Machine Learning (ICML) | June 2018
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
Information Processing in Medical Imaging (IPMI) | June 2017
Spectral Kernels for Probabilistic Analysis and Clustering of Shapes
Loic Le Folgoc, Aditya Nori, Antonio Criminisi
Information Processing in Medical Imaging (IPMI) | June 2017
Fairness as a Program Property
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
Fairness, Accountability, and Transparency in Machine Learning (FATML) | November 2016
Lifted Auto-Context Forests for Brain Tumour Segmentation
Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi
MICCAI Brain Lesion Workshop | October 2016
DeepMedic for Brain Tumor Segmentation
Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
MICCAI Brain Lesion Workshop | October 2016
Measuring Neural Net Robustness with Constraints
Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi
Neural Information Processing Systems (NIPS) | May 2016
Debugging Machine Learning Tasks
Aleksandar Chakarov, Aditya Nori, Sriram Rajamani, Shayak Sen, Deepak Vijaykeerthy
MSR-TR-2016-1135 | March 2016
A Provably Correct Sampler for Probabilistic Programs
Chung-Kil Hur, Aditya Nori, Sriram Rajamani
Foundations of Software Technology and Theoretical Computer Science (FSTTCS) | December 2015
Efficient Synthesis of Probabilistic Programs
Aditya Nori, Sherjil Ozair, Sriram Rajamani, Deepak Vijaykeerthy,
Programming Language Design and Implementation (PLDI) | June 2015
R2: An Efficient MCMC Sampler for Probabilistic Programs
Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
AAAI Conference on Artificial Intelligence (AAAI) | July 2014
Slicing Probabilistic Programs
Chung-Kil Hur, Aditya Nori, Sriram Rajamani, Selva Samuel
Programming Language Design and Implementation (PLDI) | June 2014
MUX: Algorithm Selection for Software Model Checkers
Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya Nori
Mining Software Repositories (MSR) | May 2014
Probabilistic Programming
Andy Gordon, Thomas A. Henzinger, Aditya Nori, Sriram Rajamani
International Conference on Software Engineering (ICSE Future of Software Engineering) | May 2014
Semantics Sensitive Sampling for Probabilistic Programs
Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
MSR-TR-2013-109 | October 2013
Bayesian Inference Using Data Flow Analysis
Guillaume Claret, Sriram Rajamani, Aditya Nori, Andy Gordon, Johannes Borgström
ESEC/FSE 2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering | August 2013
Termination Proofs from Tests
Aditya Nori, Rahul Sharma
Foundations of Software Engineering (FSE) | August 2013
One-bit Compressed Sensing: Provable Support and Vector Recovery
Sivakant Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
International Conference on Machine Learning (ICML) | June 2013
International Conference on Machine Learning (ICML)
Efficiently Sampling Probabilistic Programs via Program Analysis
Arun T. Chaganty, Aditya Nori, Sriram Rajamani
Artificial Intelligence and Statistics (AISTATS) | April 2013
Probabilistic Inference Using Program Analysis
Andy Gordon, Aditya Nori, Sriram Rajamani
January 2013
A Model-Learner Pattern for Bayesian Reasoning
Andrew D. Gordon, Mihhail Aizatulin, Guillaume Claret, Thore Graepel, Aditya Nori, Sriram Rajamani, Claudio Russo, Johannes Borgstroem, Andy Gordon
MSR-TR-2013-1 | January 2013
Published by Microsoft
Interpolants as Classifiers
Aditya Nori, Alex Aiken
Computer Aided Verification | July 2012
Computer Aided Verification
Interpolants as Classifiers
Rahul Sharma, Aditya Nori, Alex Aiken,
MSR-TR-2012-13 | January 2012
Probabilistic, Modular and Scalable Inference of Typestate Specifications
Nels E. Beckman, Aditya Nori
PLDI '11: Programming Languages Design and Implementation | June 2011
Measuring the Loss of Privacy from Statistics
Michael C. Tschantz, Aditya Nori
Workshop on Quantitative Analysis of Software | June 2009
Merlin: Specification Inference for Explicit Information Flow Problems
Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
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RadEdit: stress-testing biomedical vision models via diffusion image editing
Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
December 2023
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
The European Conference on Computer Vision (ECCV) | October 2022
Active label cleaning for improved dataset quality under resource constraints
Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Nature Communications | March 2022, Vol 13(1161): pp. 1-11
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot
Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002
Measuring Neural Net Robustness with Constraints
Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi
Neural Information Processing Systems (NIPS) | May 2016
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Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
2405.05299 | May 2024
Published by arXiv
Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
Nature Communications | March 2024, Vol 15
RadEdit: stress-testing biomedical vision models via diffusion image editing
Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
December 2023
Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
EMNLP 2023 | October 2023
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
Compositional Zero-Shot Domain Transfer with Text-to-Text Models
Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie Hyland
TACL 2023 | March 2023
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
The European Conference on Computer Vision (ECCV) | October 2022
Active label cleaning for improved dataset quality under resource constraints
Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Nature Communications | March 2022, Vol 13(1161): pp. 1-11
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
Secure Medical Image Analysis with CrypTFlow
Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
NeurIPS PPML Workshop | December 2020
Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
JAMA | November 2020
Towards Compliant Data Management Systems for Healthcare ML
Goutham Ramakrishnan, Aditya Nori, Hannah Richardson (nee Murfet), Pashmina Cameron
November 2020
A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
JAMA Network | June 2020, Vol 3(7)
Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot
Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002
Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot
Physics in Medicine & Biology | November 2018, Vol 63(23)
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
Information Processing in Medical Imaging (IPMI) | June 2017
Spectral Kernels for Probabilistic Analysis and Clustering of Shapes
Loic Le Folgoc, Aditya Nori, Antonio Criminisi
Information Processing in Medical Imaging (IPMI) | June 2017
Lifted Auto-Context Forests for Brain Tumour Segmentation
Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi
MICCAI Brain Lesion Workshop | October 2016
DeepMedic for Brain Tumor Segmentation
Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
MICCAI Brain Lesion Workshop | October 2016
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Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
CHI 2024 | May 2024
Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
2405.05299 | May 2024
Published by arXiv
Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety
Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Kegan, Usman Munir, Ryutaro Tanno, Hannah Richardson (nee Murfet), Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
PLOS ONE | November 2023, Vol 18(11)
Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward
Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
CHI 2023 | April 2023
A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
JAMA Network | June 2020, Vol 3(7)
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A Technique for Model-Based Testing of Classes
Aditya Nori, Ashok Sreenivas
Proceedings of the Second International Workshop on Software Engineering Tools and Techniques | January 2001
Secure Medical Image Analysis with CrypTFlow
Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
NeurIPS PPML Workshop | December 2020
Overfitting in Synthesis: Theory and Practice
Saswat Padhi, Todd Millstein, Aditya Nori, Rahul Sharma
Computer Aided Verification (CAV) | July 2019
FairSquare: Probabilistic Verification for Program Fairness
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
OOPSLA '17: OO Programming, Systems, Languages, and Applications | October 2017
Fairness as a Program Property
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
Fairness, Accountability, and Transparency in Machine Learning (FATML) | November 2016
Debugging Machine Learning Tasks
Aleksandar Chakarov, Aditya Nori, Sriram Rajamani, Shayak Sen, Deepak Vijaykeerthy
MSR-TR-2016-1135 | March 2016
A Provably Correct Sampler for Probabilistic Programs
Chung-Kil Hur, Aditya Nori, Sriram Rajamani
Foundations of Software Technology and Theoretical Computer Science (FSTTCS) | December 2015
Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances
Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
SAT '15: International Conference on Theory and Applications of Satisfiability Testing | September 2015
Learning Refinement Types
He Zhu, Aditya Nori, Suresh Jagannathan
International Conference on Functional Programming (ICFP) | August 2015
International Conference on Functional Programming (ICFP)
A User-Guided Approach to Program Analysis
Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
Foundations of Software Engineering (FSE) | August 2015
Foundations of Software Engineering (FSE) - ACM SIGSOFT Distinguished Paper
ACM SIGSOFT Distinguished Paper
Efficient Synthesis of Probabilistic Programs
Aditya Nori, Sherjil Ozair, Sriram Rajamani, Deepak Vijaykeerthy,
Programming Language Design and Implementation (PLDI) | June 2015
Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources
Venkatesh Vinayakarao, Rahul Purandare, Aditya Nori
Partial Evaluation and Program Manipulation (PEPM) | January 2015
Dependent Array Type Inference from Tests
He Zhu, Aditya Nori, Suresh Jagannathan
VMCAI '15: Verification, Model Checking and Abstract Interpretation | January 2015
R2: An Efficient MCMC Sampler for Probabilistic Programs
Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
AAAI Conference on Artificial Intelligence (AAAI) | July 2014
Slicing Probabilistic Programs
Chung-Kil Hur, Aditya Nori, Sriram Rajamani, Selva Samuel
Programming Language Design and Implementation (PLDI) | June 2014
MUX: Algorithm Selection for Software Model Checkers
Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya Nori
Mining Software Repositories (MSR) | May 2014
Probabilistic Programming
Andy Gordon, Thomas A. Henzinger, Aditya Nori, Sriram Rajamani
International Conference on Software Engineering (ICSE Future of Software Engineering) | May 2014
Bias-Variance Tradeoffs in Program Analysis
Alex Aiken, Aditya Nori, Rahul Sharma
Principles of Programming Languages (POPL) | January 2014
A Colorful Approach to Text Processing by Example
Kuat Yessenov, Shubham Tulsiani, Aditya Menon, Robert C. Miller, Sumit Gulwani, Butler Lampson, Adam Tauman Kalai
UIST '13 Proceedings of the 26th annual ACM symposium on User interface software and technology | October 2013
Semantics Sensitive Sampling for Probabilistic Programs
Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
MSR-TR-2013-109 | October 2013
Bayesian Inference Using Data Flow Analysis
Guillaume Claret, Sriram Rajamani, Aditya Nori, Andy Gordon, Johannes Borgström
ESEC/FSE 2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering | August 2013
Termination Proofs from Tests
Aditya Nori, Rahul Sharma
Foundations of Software Engineering (FSE) | August 2013
Combining Relational Learning with SMT Solvers using CEGAR
Arun Chaganty, Akash Lal, Aditya Nori, Sriram Rajamani
Computer Aided Verification (CAV) | July 2013
Verification as Learning Geometric Concepts
, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya Nori
Static Analysis Symposium (SAS) | June 2013
Static Analysis Symposium (SAS)
Efficiently Sampling Probabilistic Programs via Program Analysis
Arun T. Chaganty, Aditya Nori, Sriram Rajamani
Artificial Intelligence and Statistics (AISTATS) | April 2013
A Data Driven Approach for Algebraic Loop Invariants
, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya Nori
European Symposium on Programming (ESOP) | March 2013
Probabilistic Inference Using Program Analysis
Andy Gordon, Aditya Nori, Sriram Rajamani
January 2013
A Model-Learner Pattern for Bayesian Reasoning
Andrew D. Gordon, Mihhail Aizatulin, Guillaume Claret, Thore Graepel, Aditya Nori, Sriram Rajamani, Claudio Russo, Johannes Borgstroem, Andy Gordon
MSR-TR-2013-1 | January 2013
Published by Microsoft
Interpolants as Classifiers
Aditya Nori, Alex Aiken
Computer Aided Verification | July 2012
Computer Aided Verification
Parallelizing Top-Down Interprocedural Analyses
Aws Albarghouthi, Rahul Kumar, Aditya Nori, Sriram Rajamani
Programming Languages Design and Implementation (PLDI) | June 2012
Interpolants as Classifiers
Rahul Sharma, Aditya Nori, Alex Aiken,
MSR-TR-2012-13 | January 2012
Bottom-up shape analysis using LISF
Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori, G. Ramalingam
November 2011
Probabilistic, Modular and Scalable Inference of Typestate Specifications
Nels E. Beckman, Aditya Nori
PLDI '11: Programming Languages Design and Implementation | June 2011
Alternation for Termination
William R. Harris, Akash Lal, Aditya Nori, Sriram Rajamani
SAS '10: Static Analysis Symposium | September 2010
An Empirical Study of Optimizations in Yogi
International Conference on Software Engineering (ICSE) | May 2010
Proofs from Tests
Nels E. Beckman, Aditya Nori, Sriram Rajamani, Robert J. Simmons, Sai Deep Tetali, Aditya V. Thakur
IEEE Transactions on Software Engineering (special issue on the ISSTA 2008 best papers) | March 2010
ISSTA 2008 best papers
Compositional May-Must Program Analysis: Unleashing the Power of Alternation
Patrice Godefroid, Aditya Nori, Sriram Rajamani, Sai Deep Tetali
Principles of Programming Languages (POPL) | January 2010
Bottom-up Shape Analysis
Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori
SAS '09: Static Analysis Symposium | August 2009
Measuring the Loss of Privacy from Statistics
Michael C. Tschantz, Aditya Nori
Workshop on Quantitative Analysis of Software | June 2009
Merlin: Specification Inference for Explicit Information Flow Problems
Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
Holmes: Effective Statistical Debugging via Efficient Path Profiling
Trishul Chilimbi, Ben Liblit, Krishna Mehra, Aditya Nori, Kapil Vaswani
Proceedings of the International Conference on Software Engineering (ICSE) | May 2009
The Yogi Project: Software Property Checking via Static Analysis and Testing
Aditya Nori, Sriram Rajamani, Sai Deep Tetali, Aditya V. Thakur,
TACAS '09: Tools and Algorithms for the Construction and Analysis of Systems | March 2009
Automated Software Testing Using Program Analysis
Patrice Godefroid, Peli de Halleux, Aditya Nori, Sriram Rajamani, Wolfram Schulte, Nikolai Tillmann, Michael Y. Levin
IEEE Software, Special Issue on Software Development Tools | October 2008
Automatically Refining Abstract Interpretations
Bhargav Gulavani, Supratik Chakraborty, Aditya Nori, Sriram Rajamani
Proceedings of the 14th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) | March 2008
Quantifying the Effectiveness of Testing via Efficient Residual Path Profiling
Trishul Chilimbi, Aditya Nori, Kapil Vaswani
Proceedings of the Symposium on Foundations of Software Engineering (FSE) | September 2007
A Coset Construction for Tail-Biting Trellises
Aditya Nori, Priti Shankar
Proceedings of the International Symposium on Information Theory and its Applications (ISITA) | October 2004
Proceedings of the International Symposium on Information Theory and its Applications (ISITA)
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Secure Medical Image Analysis with CrypTFlow
Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
NeurIPS PPML Workshop | December 2020
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
Measuring the Loss of Privacy from Statistics
Michael C. Tschantz, Aditya Nori
Workshop on Quantitative Analysis of Software | June 2009
Merlin: Specification Inference for Explicit Information Flow Problems
Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
-
Compositional May-Must Program Analysis: Unleashing the Power of Alternation
Patrice Godefroid, Aditya Nori, Sriram Rajamani, Sai Deep Tetali
Principles of Programming Languages (POPL) | January 2010
Bottom-up Shape Analysis
Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori
SAS '09: Static Analysis Symposium | August 2009
Merlin: Specification Inference for Explicit Information Flow Problems
Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
SYNERGY : A New Algorithm for Property Checking
Bhargav Gulavani, Thomas Henzinger, Yamini Kannan, Aditya Nori, Sriram Rajamani
MSR-TR-2006-76 | April 2006
Exact And Approximate Algorithms for ML Decoding on Tail-Biting Trellises
Priti Shankar, Madhu A. S, Aditya Nori
March 2005
Decoding Codes on Graphs: Probabilistic Decoding
Madhu A. S, Aditya Nori
Resonance: Journal of Science Education, Indian Academy of Sciences | February 2004
Resonance: Journal of Science Education, Indian Academy of Sciences
Tail-Biting Trellises for Linear Codes and their Duals
Aditya Nori, Priti Shankar
Proceedings of the Forty-First Annual Allerton Conference on Communication, Control and Computing (Allerton) | October 2003
A BCJR-like Labeling Algorithm for Tail-Biting Trellises
Aditya Nori, Priti Shankar
Proceedings of the IEEE International Symposium on Information Theory (ISIT) | July 2003
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Preferential Path Profiling: Compactly Numbering Interesting Paths
Kapil Vaswani, Aditya Nori, Trishul Chilimbi
Proceedings of the Symposium on Principles of Programming Languages (POPL) | January 2007
-
Unifying Views of Tail-Biting Constructions for Linear Block Codes
Aditya Nori, Priti Shankar
IEEE Transactions on Information Theory | October 2006
Unifying Views of Tail-Biting Trellises for Linear Block Codes
January 2005
January 2005
Decoding Codes on Graphs: Low Density Parity Check Codes
Resonance: Journal of Science Education, Indian Academy of Sciences | September 2003
Publications by Type
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A Technique for Model-Based Testing of Classes
Aditya Nori, Ashok Sreenivas
Proceedings of the Second International Workshop on Software Engineering Tools and Techniques | January 2001
Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
NeurIPS 2024 | August 2024
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
CHI 2024 | May 2024
Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
EMNLP 2023 | October 2023
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward
Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
CHI 2023 | April 2023
Compositional Zero-Shot Domain Transfer with Text-to-Text Models
Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie Hyland
TACL 2023 | March 2023
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
The European Conference on Computer Vision (ECCV) | October 2022
Repairing Neural Networks by Leaving the Right Past Behind
Ryutaro Tanno, Melanie Fernandez Pradier, Aditya Nori, Yingzhen Li
2022 Neural Information Processing Systems | July 2022
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
Secure Medical Image Analysis with CrypTFlow
Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
NeurIPS PPML Workshop | December 2020
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
Overfitting in Synthesis: Theory and Practice
Saswat Padhi, Todd Millstein, Aditya Nori, Rahul Sharma
Computer Aided Verification (CAV) | July 2019
Autofocus Layer for Semantic Segmentation
Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori
International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018
Semi-Supervised Learning via Compact Latent Space Clustering
Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori
International Conference on Machine Learning (ICML) | June 2018
FairSquare: Probabilistic Verification for Program Fairness
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
OOPSLA '17: OO Programming, Systems, Languages, and Applications | October 2017
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
Information Processing in Medical Imaging (IPMI) | June 2017
Spectral Kernels for Probabilistic Analysis and Clustering of Shapes
Loic Le Folgoc, Aditya Nori, Antonio Criminisi
Information Processing in Medical Imaging (IPMI) | June 2017
Fairness as a Program Property
Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
Fairness, Accountability, and Transparency in Machine Learning (FATML) | November 2016
Lifted Auto-Context Forests for Brain Tumour Segmentation
Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi
MICCAI Brain Lesion Workshop | October 2016
DeepMedic for Brain Tumor Segmentation
Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
MICCAI Brain Lesion Workshop | October 2016
Measuring Neural Net Robustness with Constraints
Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi
Neural Information Processing Systems (NIPS) | May 2016
A Provably Correct Sampler for Probabilistic Programs
Chung-Kil Hur, Aditya Nori, Sriram Rajamani
Foundations of Software Technology and Theoretical Computer Science (FSTTCS) | December 2015
Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances
Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
SAT '15: International Conference on Theory and Applications of Satisfiability Testing | September 2015
Learning Refinement Types
He Zhu, Aditya Nori, Suresh Jagannathan
International Conference on Functional Programming (ICFP) | August 2015
International Conference on Functional Programming (ICFP)
A User-Guided Approach to Program Analysis
Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
Foundations of Software Engineering (FSE) | August 2015
Foundations of Software Engineering (FSE) - ACM SIGSOFT Distinguished Paper
ACM SIGSOFT Distinguished Paper
Efficient Synthesis of Probabilistic Programs
Aditya Nori, Sherjil Ozair, Sriram Rajamani, Deepak Vijaykeerthy,
Programming Language Design and Implementation (PLDI) | June 2015
Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources
Venkatesh Vinayakarao, Rahul Purandare, Aditya Nori
Partial Evaluation and Program Manipulation (PEPM) | January 2015
Dependent Array Type Inference from Tests
He Zhu, Aditya Nori, Suresh Jagannathan
VMCAI '15: Verification, Model Checking and Abstract Interpretation | January 2015
R2: An Efficient MCMC Sampler for Probabilistic Programs
Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
AAAI Conference on Artificial Intelligence (AAAI) | July 2014
Slicing Probabilistic Programs
Chung-Kil Hur, Aditya Nori, Sriram Rajamani, Selva Samuel
Programming Language Design and Implementation (PLDI) | June 2014
MUX: Algorithm Selection for Software Model Checkers
Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya Nori
Mining Software Repositories (MSR) | May 2014
Probabilistic Programming
Andy Gordon, Thomas A. Henzinger, Aditya Nori, Sriram Rajamani
International Conference on Software Engineering (ICSE Future of Software Engineering) | May 2014
Bias-Variance Tradeoffs in Program Analysis
Alex Aiken, Aditya Nori, Rahul Sharma
Principles of Programming Languages (POPL) | January 2014
A Colorful Approach to Text Processing by Example
Kuat Yessenov, Shubham Tulsiani, Aditya Menon, Robert C. Miller, Sumit Gulwani, Butler Lampson, Adam Tauman Kalai
UIST '13 Proceedings of the 26th annual ACM symposium on User interface software and technology | October 2013
Bayesian Inference Using Data Flow Analysis
Guillaume Claret, Sriram Rajamani, Aditya Nori, Andy Gordon, Johannes Borgström
ESEC/FSE 2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering | August 2013
Termination Proofs from Tests
Aditya Nori, Rahul Sharma
Foundations of Software Engineering (FSE) | August 2013
Combining Relational Learning with SMT Solvers using CEGAR
Arun Chaganty, Akash Lal, Aditya Nori, Sriram Rajamani
Computer Aided Verification (CAV) | July 2013
One-bit Compressed Sensing: Provable Support and Vector Recovery
Sivakant Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
International Conference on Machine Learning (ICML) | June 2013
International Conference on Machine Learning (ICML)
Verification as Learning Geometric Concepts
, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya Nori
Static Analysis Symposium (SAS) | June 2013
Static Analysis Symposium (SAS)
Efficiently Sampling Probabilistic Programs via Program Analysis
Arun T. Chaganty, Aditya Nori, Sriram Rajamani
Artificial Intelligence and Statistics (AISTATS) | April 2013
A Data Driven Approach for Algebraic Loop Invariants
, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya Nori
European Symposium on Programming (ESOP) | March 2013
Probabilistic Inference Using Program Analysis
Andy Gordon, Aditya Nori, Sriram Rajamani
January 2013
Interpolants as Classifiers
Aditya Nori, Alex Aiken
Computer Aided Verification | July 2012
Computer Aided Verification
Parallelizing Top-Down Interprocedural Analyses
Aws Albarghouthi, Rahul Kumar, Aditya Nori, Sriram Rajamani
Programming Languages Design and Implementation (PLDI) | June 2012
Bottom-up shape analysis using LISF
Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori, G. Ramalingam
November 2011
Probabilistic, Modular and Scalable Inference of Typestate Specifications
Nels E. Beckman, Aditya Nori
PLDI '11: Programming Languages Design and Implementation | June 2011
Alternation for Termination
William R. Harris, Akash Lal, Aditya Nori, Sriram Rajamani
SAS '10: Static Analysis Symposium | September 2010
An Empirical Study of Optimizations in Yogi
International Conference on Software Engineering (ICSE) | May 2010
Proofs from Tests
Nels E. Beckman, Aditya Nori, Sriram Rajamani, Robert J. Simmons, Sai Deep Tetali, Aditya V. Thakur
IEEE Transactions on Software Engineering (special issue on the ISSTA 2008 best papers) | March 2010
ISSTA 2008 best papers
Compositional May-Must Program Analysis: Unleashing the Power of Alternation
Patrice Godefroid, Aditya Nori, Sriram Rajamani, Sai Deep Tetali
Principles of Programming Languages (POPL) | January 2010
Bottom-up Shape Analysis
Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori
SAS '09: Static Analysis Symposium | August 2009
Measuring the Loss of Privacy from Statistics
Michael C. Tschantz, Aditya Nori
Workshop on Quantitative Analysis of Software | June 2009
Merlin: Specification Inference for Explicit Information Flow Problems
Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
Holmes: Effective Statistical Debugging via Efficient Path Profiling
Trishul Chilimbi, Ben Liblit, Krishna Mehra, Aditya Nori, Kapil Vaswani
Proceedings of the International Conference on Software Engineering (ICSE) | May 2009
The Yogi Project: Software Property Checking via Static Analysis and Testing
Aditya Nori, Sriram Rajamani, Sai Deep Tetali, Aditya V. Thakur,
TACAS '09: Tools and Algorithms for the Construction and Analysis of Systems | March 2009
Automatically Refining Abstract Interpretations
Bhargav Gulavani, Supratik Chakraborty, Aditya Nori, Sriram Rajamani
Proceedings of the 14th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) | March 2008
Quantifying the Effectiveness of Testing via Efficient Residual Path Profiling
Trishul Chilimbi, Aditya Nori, Kapil Vaswani
Proceedings of the Symposium on Foundations of Software Engineering (FSE) | September 2007
Preferential Path Profiling: Compactly Numbering Interesting Paths
Kapil Vaswani, Aditya Nori, Trishul Chilimbi
Proceedings of the Symposium on Principles of Programming Languages (POPL) | January 2007
Unifying Views of Tail-Biting Constructions for Linear Block Codes
Aditya Nori, Priti Shankar
IEEE Transactions on Information Theory | October 2006
Exact And Approximate Algorithms for ML Decoding on Tail-Biting Trellises
Priti Shankar, Madhu A. S, Aditya Nori
March 2005
A Coset Construction for Tail-Biting Trellises
Aditya Nori, Priti Shankar
Proceedings of the International Symposium on Information Theory and its Applications (ISITA) | October 2004
Proceedings of the International Symposium on Information Theory and its Applications (ISITA)
Decoding Codes on Graphs: Probabilistic Decoding
Madhu A. S, Aditya Nori
Resonance: Journal of Science Education, Indian Academy of Sciences | February 2004
Resonance: Journal of Science Education, Indian Academy of Sciences
Tail-Biting Trellises for Linear Codes and their Duals
Aditya Nori, Priti Shankar
Proceedings of the Forty-First Annual Allerton Conference on Communication, Control and Computing (Allerton) | October 2003
A BCJR-like Labeling Algorithm for Tail-Biting Trellises
Aditya Nori, Priti Shankar
Proceedings of the IEEE International Symposium on Information Theory (ISIT) | July 2003
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RadEdit: stress-testing biomedical vision models via diffusion image editing
Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
December 2023
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Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
Nature Communications | March 2024, Vol 15
Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety
Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Kegan, Usman Munir, Ryutaro Tanno, Hannah Richardson (nee Murfet), Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
PLOS ONE | November 2023, Vol 18(11)
Active label cleaning for improved dataset quality under resource constraints
Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Nature Communications | March 2022, Vol 13(1161): pp. 1-11
Artificial intelligence in healthcare: transforming the practice of medicine
Junaid Bajwa, Aditya Nori, Bryan Williams, Usman Munir
Future Healthcare Journal | July 2021
Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
JAMA | November 2020
A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
JAMA Network | June 2020, Vol 3(7)
Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot
Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002
Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot
Physics in Medicine & Biology | November 2018, Vol 63(23)
Automated Software Testing Using Program Analysis
Patrice Godefroid, Peli de Halleux, Aditya Nori, Sriram Rajamani, Wolfram Schulte, Nikolai Tillmann, Michael Y. Levin
IEEE Software, Special Issue on Software Development Tools | October 2008
Decoding Codes on Graphs: Low Density Parity Check Codes
Resonance: Journal of Science Education, Indian Academy of Sciences | September 2003
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Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
2405.05299 | May 2024
Published by arXiv
Debugging Machine Learning Tasks
Aleksandar Chakarov, Aditya Nori, Sriram Rajamani, Shayak Sen, Deepak Vijaykeerthy
MSR-TR-2016-1135 | March 2016
Semantics Sensitive Sampling for Probabilistic Programs
Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
MSR-TR-2013-109 | October 2013
A Model-Learner Pattern for Bayesian Reasoning
Andrew D. Gordon, Mihhail Aizatulin, Guillaume Claret, Thore Graepel, Aditya Nori, Sriram Rajamani, Claudio Russo, Johannes Borgstroem, Andy Gordon
MSR-TR-2013-1 | January 2013
Published by Microsoft
Interpolants as Classifiers
Rahul Sharma, Aditya Nori, Alex Aiken,
MSR-TR-2012-13 | January 2012
SYNERGY : A New Algorithm for Property Checking
Bhargav Gulavani, Thomas Henzinger, Yamini Kannan, Aditya Nori, Sriram Rajamani
MSR-TR-2006-76 | April 2006
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Towards Compliant Data Management Systems for Healthcare ML
Goutham Ramakrishnan, Aditya Nori, Hannah Richardson (nee Murfet), Pashmina Cameron
November 2020
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Unifying Views of Tail-Biting Trellises for Linear Block Codes
January 2005
January 2005