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ORCIDYulong Lu
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2020 – today
- 2026
[j13]Wuzhe Xu
, Yulong Lu, Sifan Wang, Tong-Rui Liu:
Improving data fidelity via diffusion model-based correction and super-resolution. J. Comput. Phys. 559: 114883 (2026)- [i25]Frank Cole, Dixi Wang, Yineng Chen, Yulong Lu, Rongjie Lai:
In-Context Operator Learning on the Space of Probability Measures. CoRR abs/2601.09979 (2026) - [i24]Frank Cole, Yulong Lu, Shaurya Sehgal:
A Theory of Diversity for Random Matrices with Applications to In-Context Learning of Schrödinger Equations. CoRR abs/2601.12587 (2026) - [i23]Yuxuan Zhao, Yulong Lu:
Posterior Concentration of Bayesian Physics-Informed Neural Networks for Elliptic PDEs. CoRR abs/2605.08672 (2026) - 2025
- [c8]Frank Cole, Yuxuan Zhao, Yulong Lu, Tianhao Zhang:
In-context Learning of Linear Dynamical Systems with Transformers: Approximation Bounds and Depth-separation. NeurIPS 2025 - [i22]Frank Cole, Yulong Lu, Tianhao Zhang, Yuxuan Zhao:
In-Context Learning of Linear Dynamical Systems with Transformers: Error Bounds and Depth-Separation. CoRR abs/2502.08136 (2025) - [i21]Wuzhe Xu, Yulong Lu, Lian Shen, Anqing Xuan, Ali Barzegari:
Diffusion-based Models for Unpaired Super-resolution in Fluid Dynamics. CoRR abs/2504.05443 (2025) - [i20]Yulong Lu, Pierre Monmarché:
Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games. CoRR abs/2505.07642 (2025) - [i19]Wuzhe Xu, Yulong Lu, Sifan Wang, Tong-Rui Liu:
Improving Data Fidelity via Diffusion Model-based Correction and Super-Resolution. CoRR abs/2505.08526 (2025) - [i18]Yulong Lu, Tong Mao, Jinchao Xu, Yahong Yang:
On the Dimension-Free Approximation of Deep Neural Networks for Symmetric Korobov Functions. CoRR abs/2511.12398 (2025) - 2024
- [j12]Yulong Lu, Wuzhe Xu:
Generative Downscaling of PDE Solvers with Physics-Guided Diffusion Models. J. Sci. Comput. 101(3): 71 (2024) - [j11]Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang:
Fully discretized Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem. Math. Comput. 94(356): 2723-2760 (2024) - [j10]Yahong Yang, Yulong Lu:
Near-optimal deep neural network approximation for Korobov functions with respect to Lp and H1 norms. Neural Networks 180: 106702 (2024) - [j9]Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang:
On the Convergence of Sobolev Gradient Flow for the Gross-Pitaevskii Eigenvalue Problem. SIAM J. Numer. Anal. 62(2): 667-691 (2024) - [c7]Frank Cole, Yulong Lu:
Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions. ICLR 2024 - [i17]Frank Cole, Yulong Lu:
Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian probability distributions. CoRR abs/2402.08082 (2024) - [i16]Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang:
Fully discretized Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem. CoRR abs/2403.06028 (2024) - [i15]Yulong Lu, Wuzhe Xu:
Generative downscaling of PDE solvers with physics-guided diffusion models. CoRR abs/2404.05009 (2024) - [i14]Frank Cole, Yulong Lu, Riley O'Neill, Tianhao Zhang:
Provable In-Context Learning of Linear Systems and Linear Elliptic PDEs with Transformers. CoRR abs/2409.12293 (2024) - 2023
- [c6]Wuzhe Xu, Yulong Lu, Li Wang:
Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations. AAAI 2023: 10629-10636 - [c5]Yulong Lu:
Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective. ICML 2023: 22790-22811 - [i13]Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang:
On the convergence of Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem. CoRR abs/2301.09818 (2023) - [i12]Yahong Yang, Yulong Lu:
Optimal Deep Neural Network Approximation for Korobov Functions with respect to Sobolev Norms. CoRR abs/2311.04779 (2023) - 2022
- [j8]Emmanuel Chevallier, Didong Li, Yulong Lu, David B. Dunson:
Exponential-Wrapped Distributions on Symmetric Spaces. SIAM J. Math. Data Sci. 4(4): 1347-1368 (2022) - [i11]Ziang Chen, Jianfeng Lu, Yulong Lu, Shengxuan Zhou:
A Regularity Theory for Static Schrödinger Equations on Rd in Spectral Barron Spaces. CoRR abs/2201.10072 (2022) - [i10]Wuzhe Xu, Yulong Lu, Li Wang:
Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations. CoRR abs/2212.04663 (2022) - [i9]Yulong Lu:
Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective. CoRR abs/2212.08791 (2022) - 2021
- [j7]Yulong Lu, Xingqiang Li, Yang Liu, Jiahao Leng:
The Establishment of Ore-Controlling Fracture System of Baoginshan Gold Mine Based on Fracture-Tectonic Analysis. Mob. Inf. Syst. 2021: 5887680:1-5887680:9 (2021) - [c4]Yulong Lu, Jianfeng Lu, Min Wang:
A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Partial Differential Equations. COLT 2021: 3196-3241 - [c3]Ziang Chen, Jianfeng Lu, Yulong Lu:
On the Representation of Solutions to Elliptic PDEs in Barron Spaces. NeurIPS 2021: 6454-6465 - [i8]Jianfeng Lu, Yulong Lu, Min Wang:
A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Equations. CoRR abs/2101.01708 (2021) - [i7]Jianfeng Lu, Yulong Lu:
A Priori Generalization Error Analysis of Two-Layer Neural Networks for Solving High Dimensional Schrödinger Eigenvalue Problems. CoRR abs/2105.01228 (2021) - [i6]Ziang Chen, Jianfeng Lu, Yulong Lu:
On the Representation of Solutions to Elliptic PDEs in Barron Spaces. CoRR abs/2106.07539 (2021) - [i5]Yulong Lu, Li Wang, Wuzhe Xu:
Solving multiscale steady radiative transfer equation using neural networks with uniform stability. CoRR abs/2110.07037 (2021) - 2020
- [j6]Jianfeng Lu, Yulong Lu, Zhennan Zhou:
Continuum limit and preconditioned Langevin sampling of the path integral molecular dynamics. J. Comput. Phys. 423: 109788 (2020) - [j5]Tau Shean Lim, Yulong Lu, James Nolen:
Quantitative Propagation of Chaos in a Bimolecular Chemical Reaction-Diffusion Model. SIAM J. Math. Anal. 52(2): 2098-2133 (2020) - [c2]Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying:
A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth. ICML 2020: 6426-6436 - [c1]Yulong Lu, Jianfeng Lu:
A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions. NeurIPS 2020 - [i4]Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying:
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth. CoRR abs/2003.05508 (2020) - [i3]Yulong Lu, Jianfeng Lu:
A Universal Approximation Theorem of Deep Neural Networks for Expressing Distributions. CoRR abs/2004.08867 (2020)
2010 – 2019
- 2019
- [j4]Jianfeng Lu, Yulong Lu, James Nolen:
Scaling Limit of the Stein Variational Gradient Descent: The Mean Field Regime. SIAM J. Math. Anal. 51(2): 648-671 (2019) - [i2]Yuanyuan Feng, Tingran Gao, Lei Li, Jian-Guo Liu, Yulong Lu:
Uniform-in-Time Weak Error Analysis for Stochastic Gradient Descent Algorithms via Diffusion Approximation. CoRR abs/1902.00635 (2019) - [i1]Yulong Lu, Jianfeng Lu, James Nolen:
Accelerating Langevin Sampling with Birth-death. CoRR abs/1905.09863 (2019) - 2017
- [j3]Yulong Lu, Andrew M. Stuart, Hendrik Weber:
Gaussian Approximations for Probability Measures on Rd. SIAM/ASA J. Uncertain. Quantification 5(1): 1136-1165 (2017) - [j2]Yulong Lu, Andrew M. Stuart, Hendrik Weber:
Gaussian Approximations for Transition Paths in Brownian Dynamics. SIAM J. Math. Anal. 49(4): 3005-3047 (2017) - 2011
- [j1]Huaqiang Du, Weiliang Fan, Guomo Zhou, Xiaojun Xu, Hongli Ge, Yongjun Shi, Yufeng Zhou, Ruirui Cui, Yulong Lu:
Retrieval of Canopy Closure and LAI of Moso Bamboo Forest Using Spectral Mixture Analysis Based on Real Scenario Simulation. IEEE Trans. Geosci. Remote. Sens. 49(11): 4328-4340 (2011)
Coauthor Index
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