Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
Zhong Li
Chercheur
Papiers de Collaboration
-
-
-
-
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
-
-
-
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
-
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
-