Lu, Yiping

24 publications

ICLR 2026 Physics-Informed Inference Time Scaling for Solving High-Dimensional Partial Differential Equations Zexi Fan, Yan Sun, Shihao Yang, Yiping Lu

AISTATS 2025 Randomized Iterative Solver as Iterative Refinement: A Simple Fix Towards Backward Stability Ruihan Xu, Yiping Lu

NeurIPS 2025 VAGEN: Reinforcing World Model Reasoning for Multi-Turn VLM Agents Kangrui Wang, Pingyue Zhang, Zihan Wang, Yaning Gao, Linjie Li, Qineng Wang, Hanyang Chen, Yiping Lu, Zhengyuan Yang, Lijuan Wang, Ranjay Krishna, Jiajun Wu, Li Fei-Fei, Yejin Choi, Manling Li

ICLR 2024 Generalization of Scaled Deep ResNets in the Mean-Field Regime Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher

ICML 2024 Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty Kaizhao Liu, Jose Blanchet, Lexing Ying, Yiping Lu

AAAI 2024 Statistical Spatially Inhomogeneous Diffusion Inference Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff

AISTATS 2023 Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks Huishuai Zhang, Da Yu, Yiping Lu, Di He

NeurIPSW 2023 Generalization Guarantees of Deep ResNets in the Mean-Field Regime Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher

ICLR 2023 Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin, Yiping Lu, Jose Blanchet, Lexing Ying

NeurIPS 2023 When Can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality Jose Blanchet, Haoxuan Chen, Yiping Lu, Lexing Ying

ICLR 2022 An Unconstrained Layer-Peeled Perspective on Neural Collapse Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J Su

ICLR 2022 Machine Learning for Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose Blanchet

NeurIPSW 2022 Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin, Yiping Lu, Jose Blanchet, Lexing Ying

NeurIPS 2022 Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent Yiping Lu, Jose Blanchet, Lexing Ying

NeurIPSW 2022 Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls Yiping Lu, Jiajin Li, Lexing Ying, Jose Blanchet

NeurIPSW 2021 Statistical Numerical PDE : Fast Rate, Neural Scaling Law and When It’s Optimal Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose Blanchet

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

ICLR 2020 Understanding and Improving Transformer from a Multi-Particle Dynamic System Point of View Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-Yan Liu

ICLRW 2020 Understanding and Improving Transformer from a Multi-Particle Dynamic System Point of View. Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-yan Liu

ICLR 2019 Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration Xiaoshuai Zhang, Yiping Lu, Jiaying Liu, Bin Dong

NeurIPS 2019 You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong

ICML 2018 Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations Yiping Lu, Aoxiao Zhong, Quanzheng Li, Bin Dong

ICML 2018 PDE-Net: Learning PDEs from Data Zichao Long, Yiping Lu, Xianzhong Ma, Bin Dong