Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
Zhong Li
Researcher
Publications
Publications by Year
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On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
2023 Neural Information Processing Systems | September 2023
A Brief Survey on the Approximation Theory for Sequence Modelling
Haotian Jiang, Qianxiao Li, Zhong Li, Shida Wang
Journal of Machine Learning | March 2023, Vol 2(1): pp. 1-30
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On the Approximation Properties of Recurrent Encoder-Decoder Architectures
Zhong Li, Haotian Jiang, Qianxiao Li
2022 International Conference on Learning Representations | January 2022
Spotlight
Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
Journal of Machine Learning Research | January 2022, Vol 23(42): pp. 1-85
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Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
2021 International Conference on Machine Learning | May 2021
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2021 International Conference on Learning Representations | January 2021
Publications by Research Area
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Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
2023 Neural Information Processing Systems | September 2023
A Brief Survey on the Approximation Theory for Sequence Modelling
Haotian Jiang, Qianxiao Li, Zhong Li, Shida Wang
Journal of Machine Learning | March 2023, Vol 2(1): pp. 1-30
On the Approximation Properties of Recurrent Encoder-Decoder Architectures
Zhong Li, Haotian Jiang, Qianxiao Li
2022 International Conference on Learning Representations | January 2022
Spotlight
Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
Journal of Machine Learning Research | January 2022, Vol 23(42): pp. 1-85
Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
2021 International Conference on Machine Learning | May 2021
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2021 International Conference on Learning Representations | January 2021
-
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
2023 Neural Information Processing Systems | September 2023
A Brief Survey on the Approximation Theory for Sequence Modelling
Haotian Jiang, Qianxiao Li, Zhong Li, Shida Wang
Journal of Machine Learning | March 2023, Vol 2(1): pp. 1-30
On the Approximation Properties of Recurrent Encoder-Decoder Architectures
Zhong Li, Haotian Jiang, Qianxiao Li
2022 International Conference on Learning Representations | January 2022
Spotlight
Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
Journal of Machine Learning Research | January 2022, Vol 23(42): pp. 1-85
Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
2021 International Conference on Machine Learning | May 2021
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2021 International Conference on Learning Representations | January 2021
Publications by Type
-
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
2023 Neural Information Processing Systems | September 2023
On the Approximation Properties of Recurrent Encoder-Decoder Architectures
Zhong Li, Haotian Jiang, Qianxiao Li
2022 International Conference on Learning Representations | January 2022
Spotlight
Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
2021 International Conference on Machine Learning | May 2021
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2021 International Conference on Learning Representations | January 2021
-
A Brief Survey on the Approximation Theory for Sequence Modelling
Haotian Jiang, Qianxiao Li, Zhong Li, Shida Wang
Journal of Machine Learning | March 2023, Vol 2(1): pp. 1-30
Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks
Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
Journal of Machine Learning Research | January 2022, Vol 23(42): pp. 1-85