Jianfeng Lu

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 138

Top Venues

CoRR

J. Comput. Phys.

Multiscale Model. Simul.

SIAM J. Sci. Comput.

Publications

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) (2024)
Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang
Fully discretized Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem. CoRR (2024)
Ziang Chen, Jianfeng Lu, Anru Zhang
One-Dimensional Tensor Network Recovery. SIAM J. Matrix Anal. Appl. 45 (3) (2024)
Shijun Zhang, Jianfeng Lu, Hongkai Zhao
Deep Network Approximation: Beyond ReLU to Diverse Activation Functions. CoRR (2023)
Shijun Zhang, Jianfeng Lu, Hongkai Zhao
On Enhancing Expressive Power via Compositions of Single Fixed-Size ReLU Network. ICML (2023)
Shijun Zhang, Jianfeng Lu, Hongkai Zhao
On Enhancing Expressive Power via Compositions of Single Fixed-Size ReLU Network. CoRR (2023)
Mo Zhou, Jianfeng Lu
Single Timescale Actor-Critic Method to Solve the Linear Quadratic Regulator with Convergence Guarantees. J. Mach. Learn. Res. 24 (2023)
Guillaume Bal, Simon Becker, Alexis Drouot, Clotilde Fermanian Kammerer, Jianfeng Lu, Alexander B. Watson
Edge State Dynamics Along Curved Interfaces. SIAM J. Math. Anal. 55 (5) (2023)
Mo Zhou, Jianfeng Lu
A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee. CoRR (2023)
Tanya Marwah, Ashwini Pokle, J. Zico Kolter, Zachary C. Lipton, Jianfeng Lu, Andrej Risteski
Deep Equilibrium Based Neural Operators for Steady-State PDEs. CoRR (2023)
Ziang Chen, Yingzhou Li, Jianfeng Lu
On the Global Convergence of Randomized Coordinate Gradient Descent for Nonconvex Optimization. SIAM J. Optim. 33 (2) (2023)
Xiuyuan Cheng, Jianfeng Lu, Yixin Tan, Yao Xie
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space. CoRR (2023)
Bowen Li, Jianfeng Lu
Quantum variational embedding for ground-state energy problems: sum of squares and cluster selection. CoRR (2023)
Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim
The probability flow ODE is provably fast. CoRR (2023)
Ziang Chen, Jianfeng Lu, Huajie Qian, Xinshang Wang, Wotao Yin
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent. AISTATS (2023)
Tanya Marwah, Ashwini Pokle, J. Zico Kolter, Zachary C. Lipton, Jianfeng Lu, Andrej Risteski
Deep Equilibrium Based Neural Operators for Steady-State PDEs. NeurIPS (2023)
Ziang Chen, Jianfeng Lu, Yulong Lu, Xiangxiong Zhang
On the convergence of Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem. CoRR (2023)
Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim
The probability flow ODE is provably fast. NeurIPS (2023)
Tanya Marwah, Zachary Chase Lipton, Jianfeng Lu, Andrej Risteski
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective. ICML (2023)
Holden Lee, Jianfeng Lu, Yixin Tan
Convergence of score-based generative modeling for general data distributions. ALT (2023)
Jing An, Jianfeng Lu
Convergence of stochastic gradient descent under a local Lajasiewicz condition for deep neural networks. CoRR (2023)
Hongrui Chen, Holden Lee, Jianfeng Lu
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions. ICML (2023)
Ziang Chen, Jianfeng Lu, Anru R. Zhang
One-dimensional Tensor Network Recovery. CoRR (2022)
Zhenning Cai, Di Fang, Jianfeng Lu
Asymptotic analysis of diabatic surface hopping algorithm in the adiabatic and non-adiabatic limits. CoRR (2022)
Ziang Chen, Jianfeng Lu, Yulong Lu, Shengxuan Zhou
in Spectral Barron Spaces. CoRR (2022)
Jianfeng Lu, Min Wang
Neural Network Based Variational Methods for Solving Quadratic Porous Medium Equations in High Dimensions. CoRR (2022)
Holden Lee, Jianfeng Lu, Yixin Tan
Convergence of score-based generative modeling for general data distributions. CoRR (2022)
Bowen Li, Jianfeng Lu, Ziang Yu
Vector-wise Joint Diagonalization of Almost Commuting Matrices. CoRR (2022)
Jianfeng Lu, Cody Murphey, Stefan Steinerberger
Fast Localization of Eigenfunctions via Smoothed Potentials. J. Sci. Comput. 90 (1) (2022)
Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose H. Blanchet
Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality. ICLR (2022)
Mo Zhou, Jianfeng Lu
Single Time-scale Actor-critic Method to Solve the Linear Quadratic Regulator with Convergence Guarantees. CoRR (2022)
Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin
On Representing Linear Programs by Graph Neural Networks. CoRR (2022)
Jianfeng Lu, Jeremy Louis Marzuola, Alexander B. Watson
Defect Resonances of Truncated Crystal Structures. SIAM J. Appl. Math. 82 (1) (2022)
Shi Chen, Qin Li, Jianfeng Lu, Stephen J. Wright
Manifold Learning and Nonlinear Homogenization. Multiscale Model. Simul. 20 (3) (2022)
Holden Lee, Jianfeng Lu, Yixin Tan
Convergence for score-based generative modeling with polynomial complexity. CoRR (2022)
Jianfeng Lu, Lihan Wang
Complexity of zigzag sampling algorithm for strongly log-concave distributions. Stat. Comput. 32 (3) (2022)
Hongrui Chen, Holden Lee, Jianfeng Lu
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions. CoRR (2022)
Zhenning Cai, Jianfeng Lu, Siyao Yang
Fast algorithms of bath calculations in simulations of quantum system-bath dynamics. Comput. Phys. Commun. 278 (2022)
Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin
On Representing Mixed-Integer Linear Programs by Graph Neural Networks. CoRR (2022)
Tanya Marwah, Zachary C. Lipton, Jianfeng Lu, Andrej Risteski
Neural Network Approximations of PDEs Beyond Linearity: Representational Perspective. CoRR (2022)
Zhenning Cai, Jianfeng Lu, Siyao Yang
Numerical analysis for inchworm Monte Carlo method: Sign problem and error growth. Math. Comput. 92 (341) (2022)
Holden Lee, Jianfeng Lu, Yixin Tan
Convergence for score-based generative modeling with polynomial complexity. NeurIPS (2022)
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)
Jianfeng Lu, Felix Otto
Optimal Artificial Boundary Condition for Random Elliptic Media. Found. Comput. Math. 21 (6) (2021)
Dong An, Sara Y. Cheng, Teresa Head-Gordon, Lin Lin, Jianfeng Lu
Convergence of stochastic-extended Lagrangian molecular dynamics method for polarizable force field simulation. J. Comput. Phys. 438 (2021)
Kyle Thicke, Alexander B. Watson, Jianfeng Lu
Computing Edge States without Hard Truncation. SIAM J. Sci. Comput. 43 (2) (2021)
Mo Zhou, Jiequn Han, Jianfeng Lu
Actor-Critic Method for High Dimensional Static Hamilton-Jacobi-Bellman Partial Differential Equations based on Neural Networks. SIAM J. Sci. Comput. 43 (6) (2021)
Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright
A Low-Rank Schwarz Method for Radiative Transfer Equation With Heterogeneous Scattering Coefficient. Multiscale Model. Simul. 19 (2) (2021)
Jianfeng Lu, Yulong Lu
A Priori Generalization Error Analysis of Two-Layer Neural Networks for Solving High Dimensional Schrödinger Eigenvalue Problems. CoRR (2021)
Ziang Chen, Jianfeng Lu, Yulong Lu
On the Representation of Solutions to Elliptic PDEs in Barron Spaces. NeurIPS (2021)
Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski
Efficient sampling from the Bingham distribution. ALT (2021)
Ziang Chen, Yingzhou Li, Jianfeng Lu
On the global convergence of randomized coordinate gradient descent for non-convex optimization. CoRR (2021)
Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen J. Wright
Random Coordinate Underdamped Langevin Monte Carlo. AISTATS (2021)
Mo Zhou, Jiequn Han, Jianfeng Lu
Actor-Critic Method for High Dimensional Static Hamilton-Jacobi-Bellman Partial Differential Equations based on Neural Networks. CoRR (2021)
Jianfeng Lu, Zuowei Shen, Haizhao Yang, Shijun Zhang
Deep Network Approximation for Smooth Functions. SIAM J. Math. Anal. 53 (5) (2021)
Jianfeng Lu, Yulong Lu, Min Wang
A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Equations. CoRR (2021)
Ziang Chen, Jianfeng Lu, Yulong Lu
On the Representation of Solutions to Elliptic PDEs in Barron Spaces. CoRR (2021)
Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose Blanchet
Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality. CoRR (2021)
Yuehaw Khoo, Jianfeng Lu, Lexing Ying
Efficient Construction of Tensor Ring Representations from Sampling. Multiscale Model. Simul. 19 (3) (2021)
Cheng Cheng, Ingrid Daubechies, Nadav Dym, Jianfeng Lu
Stable Phase Retrieval from Locally Stable and Conditionally Connected Measurements. CoRR (2020)
Jianfeng Lu, Stefan Steinerberger
Neural Collapse with Cross-Entropy Loss. CoRR (2020)
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 (2020)
Jianfeng Lu, Yulong Lu, Zhennan Zhou
Continuum limit and preconditioned Langevin sampling of the path integral molecular dynamics. J. Comput. Phys. 423 (2020)
Jianfeng Lu, Zuowei Shen, Haizhao Yang, Shijun Zhang
Deep Network Approximation for Smooth Functions. CoRR (2020)
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)
Shi Chen, Qin Li, Jianfeng Lu, Stephen J. Wright
Manifold Learning and Nonlinear Homogenization. CoRR (2020)
Wuchen Li, Jianfeng Lu, Li Wang
Fisher information regularization schemes for Wasserstein gradient flows. J. Comput. Phys. 416 (2020)
Victor Wen-zhe Yu, Carmen Campos, William Dawson, Alberto García, Ville Havu, Ben Hourahine, William P. Huhn, Mathias Jacquelin, Weile Jia, Murat Keçeli, Raul Laasner, Yingzhou Li, Lin Lin, Jianfeng Lu, Jonathan Moussa, José E. Román, Álvaro Vázquez-Mayagoitia, Chao Yang, Volker Blum
ELSI - An open infrastructure for electronic structure solvers. Comput. Phys. Commun. 256 (2020)
Katy Craig, Jian-Guo Liu, Jianfeng Lu, Jeremy Louis Marzuola, Li Wang
A Proximal-Gradient Algorithm for Crystal Surface Evolution. CoRR (2020)
Jiequn Han, Jianfeng Lu, Mo Zhou
Solving high-dimensional eigenvalue problems using deep neural networks: A diffusion Monte Carlo like approach. J. Comput. Phys. 423 (2020)
Jiequn Han, Jianfeng Lu, Mo Zhou
Solving high-dimensional eigenvalue problems using deep neural networks: A diffusion Monte Carlo like approach. CoRR (2020)
Ziang Chen, Yingzhou Li, Jianfeng Lu
Tensor Ring Decomposition: Optimization Landscape and One-loop Convergence of Alternating Least Squares. SIAM J. Matrix Anal. Appl. 41 (3) (2020)
Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright
Random Sampling and Efficient Algorithms for Multiscale PDEs. SIAM J. Sci. Comput. 42 (5) (2020)
Rong Ge, Holden Lee, Jianfeng Lu
Estimating normalizing constants for log-concave distributions: algorithms and lower bounds. STOC (2020)
Zhenning Cai, Jianfeng Lu, Siyao Yang
Numerical analysis for inchworm Monte Carlo method: Sign problem and error growth. CoRR (2020)
Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen J. Wright
Random Coordinate Langevin Monte Carlo. CoRR (2020)
Jianfeng Lu, Cody Murphey, Stefan Steinerberger
Fast localization of eigenfunctions via smoothed potentials. CoRR (2020)
Yulong Lu, Jianfeng Lu
A Universal Approximation Theorem of Deep Neural Networks for Expressing Distributions. CoRR (2020)
Yulong Lu, Jianfeng Lu
A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions. NeurIPS (2020)
Shahar Z. Kovalsky, Noam Aigerman, Ingrid Daubechies, Michael Kazhdan, Jianfeng Lu, Stefan Steinerberger
Non-Convex Planar Harmonic Maps. CoRR (2020)
Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski
Efficient sampling from the Bingham distribution. CoRR (2020)
Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen J. Wright
Random Coordinate Underdamped Langevin Monte Carlo. CoRR (2020)
Zhiyan Ding, Qin Li, Jianfeng Lu
Ensemble Kalman Inversion for nonlinear problems: weights, consistency, and variance bounds. CoRR (2020)
Jianfeng Lu, Alexander B. Watson, Michael I. Weinstein
Dirac Operators and Domain Walls. SIAM J. Math. Anal. 52 (2) (2020)
Jianfeng Lu, Zhe Wang
The Full Configuration Interaction Quantum Monte Carlo Method through the Lens of Inexact Power Iteration. SIAM J. Sci. Comput. 42 (1) (2020)
Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright
Randomized Sampling for Basis Function Construction in Generalized Finite Element Methods. Multiscale Model. Simul. 18 (2) (2020)
Yingzhou Li, Jianfeng Lu, Anqi Mao
Variational training of neural network approximations of solution maps for physical models. J. Comput. Phys. 409 (2020)
Lin Lin, Jianfeng Lu, Lexing Ying
Numerical methods for Kohn-Sham density functional theory. Acta Numer. 28 (2019)
Hongxu Chen, Qin Li, Jianfeng Lu
A numerical method for coupling the BGK model and Euler equations through the linearized Knudsen layer. J. Comput. Phys. 398 (2019)
Jiequn Han, Yingzhou Li, Lin Lin, Jianfeng Lu, Jiefu Zhang, Linfeng Zhang
Universal approximation of symmetric and anti-symmetric functions. CoRR (2019)
Yingzhou Li, Jianfeng Lu, Zhe Wang
CoordinateWise Descent Methods for Leading Eigenvalue Problem. SIAM J. Sci. Comput. 41 (4) (2019)
Yulong Lu, Jianfeng Lu, James Nolen
Accelerating Langevin Sampling with Birth-death. CoRR (2019)
Wuchen Li, Jianfeng Lu, Li Wang
Fisher information regularization schemes for Wasserstein gradient flows. CoRR (2019)
Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright
A low-rank Schwarz method for radiative transport equation with heterogeneous scattering coefficient. CoRR (2019)
Yingzhou Li, Jianfeng Lu, Anqi Mao
Variational training of neural network approximations of solution maps for physical models. CoRR (2019)
Ludwig Gauckler, Jianfeng Lu, Jeremy Louis Marzuola, Frederic Rousset, Katharina Schratz
Trigonometric integrators for quasilinear wave equations. Math. Comput. 88 (316) (2019)
Lei Li, Jian-Guo Liu, Zibu Liu, Jianfeng Lu
A stochastic version of Stein Variational Gradient Descent for efficient sampling. CoRR (2019)
Rong Ge, Holden Lee, Jianfeng Lu
Estimating Normalizing Constants for Log-Concave Distributions: Algorithms and Lower Bounds. CoRR (2019)
Wei Zhu, Qiang Qiu, Bao Wang, Jianfeng Lu, Guillermo Sapiro, Ingrid Daubechies
Stop Memorizing: A Data-Dependent Regularization Framework for Intrinsic Pattern Learning. SIAM J. Math. Data Sci. 1 (3) (2019)
Jianfeng Lu, Yulong Lu, James Nolen
Scaling Limit of the Stein Variational Gradient Descent: The Mean Field Regime. SIAM J. Math. Anal. 51 (2) (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jianfeng Lu