Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality on Hölder Class. - Yuling Jiao; Yanming Lai; Xiliang Lu; Jerry Zhijian Yang (CoRR, 2021)

Convergence Rate Analysis for Deep Ritz Method. - Chenguang Duan; Yuling Jiao; Yanming Lai; Xiliang Lu; Jerry Zhijian Yang (CoRR, 2021)

Error Analysis of Deep Ritz Methods for Elliptic Equations. - Yuling Jiao; Yanming Lai; Yisu Luo; Yang Wang 020; Yunfei Yang 002 (CoRR, 2021)

Convergence Analysis for the PINNs. - Yuling Jiao; Yanming Lai; Dingwei Li; Xiliang Lu; Yang Wang; Jerry Zhijian Yang (CoRR, 2021)

Analysis of Deep Ritz Methods for Laplace Equations with Dirichlet Boundary Conditions. - Chenguang Duan; Yuling Jiao; Yanming Lai; Xiliang Lu; Qimeng Quan; Jerry Zhijian Yang (CoRR, 2021)

Convergence Analysis of the Deep Galerkin Method for Weak Solutions. - Yuling Jiao; Yanming Lai; Yang Wang 020; Haizhao Yang; Yunfei Yang 002 (CoRR, 2023)

Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on Hölder Class. - Yuling Jiao; Yanming Lai; Xiliang Lu; Fengru Wang; Jerry Zhijian Yang; Yuanyuan Yang (SIAM J. Math. Anal., 2023)

Convergence Analysis of Flow Matching in Latent Space with Transformers. - Yuling Jiao; Yanming Lai; Yang Wang 020; Bokai Yan (CoRR, 2024)

Error Analysis of Three-Layer Neural Network Trained with PGD for Deep Ritz Method. - Yuling Jiao; Yanming Lai; Yang Wang (CoRR, 2024)

Approximation Bounds for Transformer Networks with Application to Regression. - Yuling Jiao; Yanming Lai; Defeng Sun; Yang Wang; Bokai Yan (CoRR, 2025)

Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective. - Yuling Jiao; Yanming Lai; Yang Wang; Bokai Yan (CoRR, 2025)

Error Analysis of Three-Layer Neural Network Trained With PGD for Deep Ritz Method. - Yuling Jiao; Yanming Lai; Yang Wang 020 (IEEE Trans. Inf. Theory, 2025)