Lu, Yulong

10 publications

NeurIPS 2025 In-Context Learning of Linear Dynamical Systems with Transformers: Approximation Bounds and Depth-Separation Frank Cole, Yuxuan Zhao, Yulong Lu, Tianhao Zhang

NeurIPSW 2024 Provable In-Context Learning of Linear Systems and Linear Elliptic PDEs with Transformers Frank Cole, Yulong Lu, Tianhao Zhang, Riley C. W. O'Neill

ICLR 2024 Score-Based Generative Models Break the Curse of Dimensionality in Learning a Family of Sub-Gaussian Distributions Frank Cole, Yulong Lu

AAAI 2023 Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations Wuzhe Xu, Yulong Lu, Li Wang

ICML 2023 Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective Yulong Lu

COLT 2021 A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Partial Differential Equations Yulong Lu, Jianfeng Lu, Min Wang

NeurIPS 2021 On the Representation of Solutions to Elliptic PDEs in Barron Spaces Ziang Chen, Jianfeng Lu, Yulong Lu

ICML 2020 A Mean Field Analysis of Deep ResNet and Beyond: Towards Provably Optimization via Overparameterization from Depth Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying

ICLRW 2020 A Mean-Field Analysis of Deep ResNet and Beyond:Towards Provable Optimization via Overparameterization from Depth Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying

NeurIPS 2020 A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions Yulong Lu, Jianfeng Lu