Neural Structure Learning with Stochastic Differential Equations
Benjie Wang, Joel Jennings, Wenbo Gong
ICLR 2024 | November 2023
Wenbo Gong
Senior Researcher
Publications
Publications by Year
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Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Rhino: Deep Causal Temporal Relationship Learning with history-dependent noise
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Simultaneous Missing Value Imputation and Structure Learning with Groups
Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
2022 Neural Information Processing Systems | February 2022
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Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model
Wenbo Gong, Sebastian Tschiatschek, Richard Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | August 2019
Publications by Research Area
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Neural Structure Learning with Stochastic Differential Equations
Benjie Wang, Joel Jennings, Wenbo Gong
ICLR 2024 | November 2023
Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Rhino: Deep Causal Temporal Relationship Learning with history-dependent noise
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Simultaneous Missing Value Imputation and Structure Learning with Groups
Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
2022 Neural Information Processing Systems | February 2022
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model
Wenbo Gong, Sebastian Tschiatschek, Richard Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | August 2019
Publications by Type
-
Neural Structure Learning with Stochastic Differential Equations
Benjie Wang, Joel Jennings, Wenbo Gong
ICLR 2024 | November 2023
Deep End-to-end Causal Inference
Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Rhino: Deep Causal Temporal Relationship Learning with history-dependent noise
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
Simultaneous Missing Value Imputation and Structure Learning with Groups
Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
2022 Neural Information Processing Systems | February 2022
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model
Wenbo Gong, Sebastian Tschiatschek, Richard Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang
Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | August 2019