Yulong Lu - RankMe

42 papers A* 7Journal 35

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Theory of Diversity for Random Matrices with Applications to In-Context Learning of Schrödinger Equations. CoRR Frank Cole, Yulong Lu, Shaurya Sehgal
2026	J	`jnl`	In-Context Operator Learning on the Space of Probability Measures. CoRR Frank Cole, Dixi Wang, Yineng Chen, Yulong Lu, Rongjie Lai
2025	J	`jnl`	Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games. CoRR Yulong Lu, Pierre Monmarché
2025	J	`jnl`	Diffusion-based Models for Unpaired Super-resolution in Fluid Dynamics. CoRR Wuzhe Xu, Yulong Lu, Lian Shen, Anqing Xuan, Ali Barzegari
2025	J	`jnl`	Improving Data Fidelity via Diffusion Model-based Correction and Super-Resolution. CoRR Wuzhe Xu, Yulong Lu, Sifan Wang, Tong-Rui Liu
2025	J	`jnl`	In-Context Learning of Linear Dynamical Systems with Transformers: Error Bounds and Depth-Separation. CoRR Frank Cole, Yulong Lu, Tianhao Zhang, Yuxuan Zhao
2025	J	`jnl`	On the Dimension-Free Approximation of Deep Neural Networks for Symmetric Korobov Functions. CoRR Yulong Lu, Tong Mao, Jinchao Xu, Yahong Yang
2024	J	`jnl`	Fully discretized Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem. CoRR Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang
2024	J	`jnl`	Generative Downscaling of PDE Solvers with Physics-Guided Diffusion Models. J. Sci. Comput. Yulong Lu, Wuzhe Xu
2024	J	`jnl`	Generative downscaling of PDE solvers with physics-guided diffusion models. CoRR Yulong Lu, Wuzhe Xu
2024	J	`jnl`	Near-optimal deep neural network approximation for Korobov functions with respect to Lp and H1 norms. Neural Networks Yahong Yang, Yulong Lu
2024	J	`jnl`	On the Convergence of Sobolev Gradient Flow for the Gross-Pitaevskii Eigenvalue Problem. SIAM J. Numer. Anal. Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang
2024	J	`jnl`	Provable In-Context Learning of Linear Systems and Linear Elliptic PDEs with Transformers. CoRR Frank Cole, Yulong Lu, Riley O'Neill, Tianhao Zhang
2024	A*	`conf`	Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions. ICLR Frank Cole, Yulong Lu
2024	J	`jnl`	Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian probability distributions. CoRR Frank Cole, Yulong Lu
2023	J	`jnl`	On the convergence of Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem. CoRR Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang
2023	J	`jnl`	Optimal Deep Neural Network Approximation for Korobov Functions with respect to Sobolev Norms. CoRR Yahong Yang, Yulong Lu
2023	A*	`conf`	Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations. AAAI Wuzhe Xu, Yulong Lu, Li Wang
2023	A*	`conf`	Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective. ICML Yulong Lu
2022	J	`jnl`	A Regularity Theory for Static Schrödinger Equations on R CoRR Ziang Chen, Jianfeng Lu, Yulong Lu, Shengxuan Zhou
2022	J	`jnl`	Exponential-Wrapped Distributions on Symmetric Spaces. SIAM J. Math. Data Sci. Emmanuel Chevallier, Didong Li, Yulong Lu, David B. Dunson
2022	J	`jnl`	Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations. CoRR Wuzhe Xu, Yulong Lu, Li Wang
2022	J	`jnl`	Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective. CoRR Yulong Lu
2021	J	`jnl`	A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Equations. CoRR Jianfeng Lu, Yulong Lu, Min Wang
2021	A*	`conf`	A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Partial Differential Equations. COLT Yulong Lu, Jianfeng Lu, Min Wang
2021	J	`jnl`	A Priori Generalization Error Analysis of Two-Layer Neural Networks for Solving High Dimensional Schrödinger Eigenvalue Problems. CoRR Jianfeng Lu, Yulong Lu
2021	A*	`conf`	On the Representation of Solutions to Elliptic PDEs in Barron Spaces. NeurIPS Ziang Chen, Jianfeng Lu, Yulong Lu
2021	J	`jnl`	On the Representation of Solutions to Elliptic PDEs in Barron Spaces. CoRR Ziang Chen, Jianfeng Lu, Yulong Lu
2021	J	`jnl`	Solving multiscale steady radiative transfer equation using neural networks with uniform stability. CoRR Yulong Lu, Li Wang, Wuzhe Xu
2021	J	`jnl`	The Establishment of Ore-Controlling Fracture System of Baoginshan Gold Mine Based on Fracture-Tectonic Analysis. Mob. Inf. Syst. Yulong Lu, Xingqiang Li, Yang Liu, Jiahao Leng
2020	A*	`conf`	A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth. ICML Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying
2020	J	`jnl`	A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth. CoRR Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying
2020	J	`jnl`	A Universal Approximation Theorem of Deep Neural Networks for Expressing Distributions. CoRR Yulong Lu, Jianfeng Lu
2020	A*	`conf`	A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions. NeurIPS Yulong Lu, Jianfeng Lu
2020	J	`jnl`	Continuum limit and preconditioned Langevin sampling of the path integral molecular dynamics. J. Comput. Phys. Jianfeng Lu, Yulong Lu, Zhennan Zhou
2020	J	`jnl`	Quantitative Propagation of Chaos in a Bimolecular Chemical Reaction-Diffusion Model. SIAM J. Math. Anal. Tau Shean Lim, Yulong Lu, James Nolen
2019	J	`jnl`	Accelerating Langevin Sampling with Birth-death. CoRR Yulong Lu, Jianfeng Lu, James Nolen
2019	J	`jnl`	Scaling Limit of the Stein Variational Gradient Descent: The Mean Field Regime. SIAM J. Math. Anal. Jianfeng Lu, Yulong Lu, James Nolen
2019	J	`jnl`	Uniform-in-Time Weak Error Analysis for Stochastic Gradient Descent Algorithms via Diffusion Approximation. CoRR Yuanyuan Feng, Tingran Gao, Lei Li, Jian-Guo Liu, Yulong Lu
2017	J	`jnl`	Gaussian Approximations for Probability Measures on R SIAM/ASA J. Uncertain. Quantification Yulong Lu, Andrew M. Stuart, Hendrik Weber
2017	J	`jnl`	Gaussian Approximations for Transition Paths in Brownian Dynamics. SIAM J. Math. Anal. Yulong Lu, Andrew M. Stuart, Hendrik Weber
2011	J	`jnl`	Retrieval of Canopy Closure and LAI of Moso Bamboo Forest Using Spectral Mixture Analysis Based on Real Scenario Simulation. IEEE Trans. Geosci. Remote. Sens. Huaqiang Du, Weiliang Fan, Guomo Zhou, Xiaojun Xu, Hongli Ge, Yongjun Shi, Yufeng Zhou, Ruirui Cui, Yulong Lu