Publications of Jianfeng Lu    :chronological  alphabetical  combined  bibtex listing:

Papers Published
  1. Chen, Z; Lu, J; Lu, Y; Zhang, X, On the Convergence of Sobolev Gradient Flow for the Gross–Pitaevskii Eigenvalue Problem, SIAM Journal on Numerical Analysis, vol. 62 no. 2 (April, 2024), pp. 667-691, Society for Industrial & Applied Mathematics (SIAM) [doi] .
  2. Li, X; Pura, J; Allen, A; Owzar, K; Lu, J; Harms, M; Xie, J, DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree., Genet Epidemiol, vol. 48 no. 1 (February, 2024), pp. 42-55 [doi] [abs] .
  3. Jing, Y; Chen, J; Li, L; Lu, J, A Machine Learning Framework for Geodesics Under Spherical Wasserstein–Fisher–Rao Metric and Its Application for Weighted Sample Generation, Journal of Scientific Computing, vol. 98 no. 1 (January, 2024) [doi] [abs] .
  4. Wang, Z; Zhang, Z; Lu, J; Li, Y, Coordinate Descent Full Configuration Interaction for Excited States., Journal of chemical theory and computation, vol. 19 no. 21 (November, 2023), pp. 7731-7739 [doi] [abs] .
  5. Cao, Y; Lu, J; Wang, L, On Explicit L2 -Convergence Rate Estimate for Underdamped Langevin Dynamics, Archive for Rational Mechanics and Analysis, vol. 247 no. 5 (October, 2023) [doi] [abs] .
  6. Lu, J; Wu, Y; Xiang, Y, Score-based Transport Modeling for Mean-Field Fokker-Planck Equations, vol. 503 (April, 2023) [doi] [abs] .
  7. Wang, M; Lu, J, Neural Network-Based Variational Methods for Solving Quadratic Porous Medium Equations in High Dimensions, Communications in Mathematics and Statistics, vol. 11 no. 1 (March, 2023), pp. 21-57 [doi] [abs] .
  8. Bierman, J; Li, Y; Lu, J, Improving the Accuracy of Variational Quantum Eigensolvers with Fewer Qubits Using Orbital Optimization., Journal of chemical theory and computation, vol. 19 no. 3 (February, 2023), pp. 790-798 [doi] [abs] .
  9. Cai, Z; Lu, J; Yang, S, NUMERICAL ANALYSIS FOR INCHWORM MONTE CARLO METHOD: SIGN PROBLEM AND ERROR GROWTH, Mathematics of Computation, vol. 92 no. 341 (January, 2023), pp. 1141-1209, American Mathematical Society (AMS) [doi] [abs] .
  10. Chen, Z; Lu, J; Lu, Y; Zhou, S, A REGULARITY THEORY FOR STATIC SCHRÖDINGER EQUATIONS ON R d IN SPECTRAL BARRON SPACES, SIAM Journal on Mathematical Analysis, vol. 55 no. 1 (January, 2023), pp. 557-570 [doi] [abs] .
  11. Chen, Z; Lu, J; Qian, H; Wang, X; Yin, W, HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent, Proceedings of Machine Learning Research, vol. 206 (January, 2023), pp. 10732-10781 [abs] .
  12. Lee, H; Lu, J; Tan, Y, Convergence of score-based generative modeling for general data distributions, Proceedings of Machine Learning Research, vol. 201 (January, 2023), pp. 946-985 [abs] .
  13. Chen, Z; Li, Y; Lu, J, ON THE GLOBAL CONVERGENCE OF RANDOMIZED COORDINATE GRADIENT DESCENT FOR NONCONVEX OPTIMIZATION*, SIAM Journal on Optimization, vol. 33 no. 2 (January, 2023), pp. 713-738 [doi] [abs] .
  14. Sachs, M; Sen, D; Lu, J; Dunson, D, Posterior Computation with the Gibbs Zig-Zag Sampler, Bayesian Analysis, vol. 18 no. 3 (January, 2023), pp. 909-927 [doi] [abs] .
  15. Huang, H; Landsberg, JM; Lu, J, GEOMETRY OF BACKFLOW TRANSFORMATION ANSATZE FOR QUANTUM MANY-BODY FERMIONIC WAVEFUNCTIONS, Communications in Mathematical Sciences, vol. 21 no. 5 (January, 2023), pp. 1447-1453 [doi] [abs] .
  16. Bal, G; Becker, S; Drouot, A; Kammerer, CF; Lu, J; Watson, AB, EDGE STATE DYNAMICS ALONG CURVED INTERFACES, SIAM Journal on Mathematical Analysis, vol. 55 no. 5 (January, 2023), pp. 4219-4254 [doi] [abs] .
  17. Zhang, S; Lu, J; Zhao, H, On Enhancing Expressive Power via Compositions of Single Fixed-Size ReLU Network, Proceedings of Machine Learning Research, vol. 202 (January, 2023), pp. 41452-41487 [abs] .
  18. Chen, H; Lee, H; Lu, J, Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions, Proceedings of Machine Learning Research, vol. 202 (January, 2023), pp. 5367-5382 [abs] .
  19. Agazzi, A; Lu, J; Mukherjee, S, Global optimality of Elman-type RNNs in the mean-field regime, Proceedings of Machine Learning Research, vol. 202 (January, 2023), pp. 196-227 [abs] .
  20. Marwah, T; Lipton, ZC; Lu, J; Risteski, A, Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective, Proceedings of Machine Learning Research, vol. 202 (January, 2023), pp. 24139-24172 [abs] .
  21. Holst, M; Hu, H; Lu, J; Marzuola, JL; Song, D; Weare, J, Symmetry Breaking and the Generation of Spin Ordered Magnetic States in Density Functional Theory Due to Dirac Exchange for a Hydrogen Molecule, Journal of Nonlinear Science, vol. 32 no. 6 (December, 2022) [doi] [abs] .
  22. Craig, K; Liu, JG; Lu, J; Marzuola, JL; Wang, L, A proximal-gradient algorithm for crystal surface evolution, Numerische Mathematik, vol. 152 no. 3 (November, 2022), pp. 631-662 [doi] [abs] .
  23. Cai, Z; Lu, J; Yang, S, Fast algorithms of bath calculations in simulations of quantum system-bath dynamics, Computer Physics Communications, vol. 278 (September, 2022) [doi] [abs] .
  24. Barthel, T; Lu, J; Friesecke, G, On the closedness and geometry of tensor network state sets, Letters in Mathematical Physics, vol. 112 no. 4 (August, 2022) [doi] [abs] .
  25. Bierman, J; Li, Y; Lu, J, Quantum Orbital Minimization Method for Excited States Calculation on a Quantum Computer., Journal of chemical theory and computation, vol. 18 no. 8 (August, 2022), pp. 4674-4689 [doi] [abs] .
  26. Lu, J; Steinerberger, S, Neural collapse under cross-entropy loss, Applied and Computational Harmonic Analysis, vol. 59 (July, 2022), pp. 224-241 [doi] [abs] .
  27. Lu, J; Wang, L, Complexity of zigzag sampling algorithm for strongly log-concave distributions, Statistics and Computing, vol. 32 no. 3 (June, 2022) [doi] [abs] .
  28. Pescia, G; Han, J; Lovato, A; Lu, J; Carleo, G, Neural-network quantum states for periodic systems in continuous space, Physical Review Research, vol. 4 no. 2 (June, 2022) [doi] [abs] .
  29. Chen, K; Chen, S; Li, Q; Lu, J; Wright, S, Low-Rank Approximation for Multiscale PDEs, Notices of the American Mathematical Society, vol. 69 no. 6 (June, 2022), pp. 901-913 [doi] .
  30. Lu, J; Wang, L, ON EXPLICIT L2-CONVERGENCE RATE ESTIMATE FOR PIECEWISE DETERMINISTIC MARKOV PROCESSES IN MCMC ALGORITHMS, Annals of Applied Probability, vol. 32 no. 2 (April, 2022), pp. 1333-1361 [doi] [abs] .
  31. Lu, J; Stubbs, KD; Watson, AB, Existence and Computation of Generalized Wannier Functions for Non-Periodic Systems in Two Dimensions and Higher, Archive for Rational Mechanics and Analysis, vol. 243 no. 3 (March, 2022), pp. 1269-1323 [doi] [abs] .
  32. Lu, J; Murphey, C; Steinerberger, S, Fast Localization of Eigenfunctions via Smoothed Potentials, Journal of Scientific Computing, vol. 90 no. 1 (January, 2022) [doi] [abs] .
  33. Lu, J; Marzuola, JL; Watson, AB, DEFECT RESONANCES OF TRUNCATED CRYSTAL STRUCTURES, SIAM Journal on Applied Mathematics, vol. 82 no. 1 (January, 2022), pp. 49-74, Society for Industrial & Applied Mathematics (SIAM) [doi] [abs] .
  34. Lu, J; Zhang, Z; Zhou, Z, Bloch dynamics with second order Berry phase correction, Asymptotic Analysis, vol. 128 no. 1 (January, 2022), pp. 55-84 [doi] [abs] .
  35. Han, J; Li, Y; Lin, L; Lu, J; Zhang, J; Zhang, L, UNIVERSAL APPROXIMATION OF SYMMETRIC AND ANTI-SYMMETRIC FUNCTIONS, Communications in Mathematical Sciences, vol. 20 no. 5 (January, 2022), pp. 1397-1408 [doi] [abs] .
  36. Chen, S; Li, Q; Lu, J; Wright, SJ, MANIFOLD LEARNING AND NONLINEAR HOMOGENIZATION, Multiscale Modeling and Simulation, vol. 20 no. 3 (January, 2022), pp. 1093-1126 [doi] [abs] .
  37. Lu, Y; Chen, H; Lu, J; Ying, L; Blanchet, J, MACHINE LEARNING FOR ELLIPTIC PDES: FAST RATE GENERALIZATION BOUND, NEURAL SCALING LAW AND MINIMAX OPTIMALITY, ICLR 2022 - 10th International Conference on Learning Representations (January, 2022) [abs] .
  38. Lee, H; Lu, J; Tan, Y, Convergence for score-based generative modeling with polynomial complexity, Advances in Neural Information Processing Systems, vol. 35 (January, 2022) [abs] .
  39. Lu, J; Otto, F, Optimal Artificial Boundary Condition for Random Elliptic Media, Foundations of Computational Mathematics, vol. 21 no. 6 (December, 2021), pp. 1643-1702 [doi] [abs] .
  40. Chen, K; Chen, S; Li, Q; Lu, J; Wright, SJ, Low-rank approximation for multiscale PDEs (November, 2021) [abs] .
  41. Huang, H; Landsberg, JM; Lu, J, Geometry of backflow transformation ansatz for quantum many-body fermionic wavefunctions (November, 2021) [abs] .
  42. Cheng, C; Daubechies, I; Dym, N; Lu, J, Stable phase retrieval from locally stable and conditionally connected measurements, Applied and Computational Harmonic Analysis, vol. 55 (November, 2021), pp. 440-465 [doi] [abs] .
  43. Lu, J; Otto, F; Wang, L, Optimal artificial boundary conditions based on second-order correctors for three dimensional random elliptic media (September, 2021) [abs] .
  44. Ding, Z; Li, Q; Lu, J, ENSEMBLE KALMAN INVERSION FOR NONLINEAR PROBLEMS: WEIGHTS, CONSISTENCY, AND VARIANCE BOUNDS, Foundations of Data Science, vol. 3 no. 3 (September, 2021), pp. 371-411 [doi] [abs] .
  45. Li, L; Goodrich, C; Yang, H; Phillips, KR; Jia, Z; Chen, H; Wang, L; Zhong, J; Liu, A; Lu, J; Shuai, J; Brenner, MP; Spaepen, F; Aizenberg, J, Microscopic origins of the crystallographically preferred growth in evaporation-induced colloidal crystals., Proceedings of the National Academy of Sciences of the United States of America, vol. 118 no. 32 (August, 2021), pp. e2107588118 [doi] [abs] .
  46. An, D; Cheng, SY; Head-Gordon, T; Lin, L; Lu, J, Convergence of stochastic-extended Lagrangian molecular dynamics method for polarizable force field simulation, Journal of Computational Physics, vol. 438 (August, 2021) [doi] [abs] .
  47. Lu, J; Stubbs, KD, Algebraic localization of Wannier functions implies Chern triviality in non-periodic insulators (July, 2021) [abs] .
  48. Chen, Z; Lu, J; Lu, Y, On the Representation of Solutions to Elliptic PDEs in Barron Spaces (June, 2021) [abs] .
  49. Khoo, Y; Lu, J; Ying, L, Solving parametric PDE problems with artificial neural networks, European Journal of Applied Mathematics, vol. 32 no. 3 (June, 2021), pp. 421-435 [doi] [abs] .
  50. Yang, S; Cai, Z; Lu, J, Inclusion-exclusion principle for open quantum systems with bosonic bath, New Journal of Physics, vol. 23 no. 6 (June, 2021) [doi] [abs] .
  51. Bal, G; Becker, S; Drouot, A; Kammerer, CF; Lu, J; Watson, A, Edge state dynamics along curved interfaces (June, 2021) [abs] .
  52. Lu, J; Lu, Y, A Priori Generalization Error Analysis of Two-Layer Neural Networks for Solving High Dimensional Schrödinger Eigenvalue Problems (May, 2021) [abs] .
  53. Lu, J; Steinerberger, S, Optimal Trapping for Brownian Motion: a Nonlinear Analogue of the Torsion Function, Potential Analysis, vol. 54 no. 4 (April, 2021), pp. 687-698 [doi] [abs] .
  54. Coffman, AJ; Lu, J; Subotnik, JE, A grid-free approach for simulating sweep and cyclic voltammetry., The Journal of chemical physics, vol. 154 no. 16 (April, 2021), pp. 161101 [doi] [abs] .
  55. Thicke, K; Watson, AB; Lu, J, Computing edge states without hard truncation, SIAM Journal on Scientific Computing, vol. 43 no. 2 (March, 2021), pp. B323-B353 [doi] [abs] .
  56. Cao, Y; Lu, J, Structure-preserving numerical schemes for Lindblad equations (March, 2021) [abs] .
  57. Stubbs, KD; Watson, AB; Lu, J, Iterated projected position algorithm for constructing exponentially localized generalized Wannier functions for periodic and nonperiodic insulators in two dimensions and higher, Physical Review B, vol. 103 no. 7 (February, 2021) [doi] [abs] .
  58. Lu, J; Stubbs, KD, Algebraic localization implies exponential localization in non-periodic insulators (January, 2021) [abs] .
  59. Lu, J; Lu, Y; Wang, M, A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Equations (January, 2021) [abs] .
  60. Chen, Z; Li, Y; Lu, J, On the global convergence of randomized coordinate gradient descent for non-convex optimization (January, 2021) [abs] .
  61. Li, L; Lu, J; Mattingly, JC; Wang, L, Numerical Methods For Stochastic Differential Equations Based On Gaussian Mixture, Communications in Mathematical Sciences, vol. 19 no. 6 (January, 2021), pp. 1549-1577, International Press of Boston [doi] [abs] .
  62. Zhou, M; Han, J; Lu, J, ACTOR-CRITIC METHOD FOR HIGH DIMENSIONAL STATIC HAMILTON-JACOBI-BELLMAN PARTIAL DIFFERENTIAL EQUATIONS BASED ON NEURAL NETWORKS, SIAM Journal on Scientific Computing, vol. 43 no. 6 (January, 2021), pp. A4043-A4066, Society for Industrial & Applied Mathematics (SIAM) [doi] [abs] .
  63. Lu, J; Shen, Z; Yang, H; Zhang, S, DEEP NETWORK APPROXIMATION FOR SMOOTH FUNCTIONS, SIAM Journal on Mathematical Analysis, vol. 53 no. 5 (January, 2021), pp. 5465-5506, Society for Industrial & Applied Mathematics (SIAM) [doi] [abs] .
  64. Cao, Y; Lu, J; Wang, L, COMPLEXITY OF RANDOMIZED ALGORITHMS FOR UNDERDAMPED LANGEVIN DYNAMICS*, Communications in Mathematical Sciences, vol. 19 no. 7 (January, 2021), pp. 1827-1853, International Press of Boston [doi] [abs] .
  65. Khoo, Y; Lu, J; Ying, L, Efficient construction of tensor ring representations from sampling, Multiscale Modeling and Simulation, vol. 19 no. 3 (January, 2021) [doi] [abs] .
  66. Loring, TA; Lu, J; Watson, AB, Locality of the windowed local density of states, Discussion Contributions 10th Vienna Conference on Mathematical Modelling, volume 17. ARGESIM, 2022 (January, 2021) [abs] .
  67. Chen, K; Li, Q; Lu, J; Wright, SJ, A low-rank schwarz method for radiative transfer equation with heterogeneous scattering coefficient, Multiscale Modeling and Simulation, vol. 19 no. 2 (January, 2021), pp. 775-801 [doi] [abs] .
  68. Chen, Z; Lu, J; Lu, Y, On the Representation of Solutions to Elliptic PDEs in Barron Spaces, Advances in Neural Information Processing Systems, vol. 8 (January, 2021), pp. 6454-6465 [abs] .
  69. Ge, R; Lee, H; Lu, J; Risteski, A, Efficient sampling from the Bingham distribution, Proceedings of Machine Learning Research, vol. 132 (January, 2021), pp. 673-685 [abs] .
  70. Lu, J; Lu, Y; Wang, M, A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Partial Differential Equations, Proceedings of Machine Learning Research, vol. 134 (January, 2021), pp. 3196-3241 [abs] .
  71. Agazzi, A; Lu, J, Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes, Proceedings of Machine Learning Research, vol. 145 (January, 2021), pp. 37-74 [abs] .
  72. Gao, Y; Katsevich, AE; Liu, JG; Lu, J; Marzuola, JL, ANALYSIS OF A FOURTH-ORDER EXPONENTIAL PDE ARISING FROM A CRYSTAL SURFACE JUMP PROCESS WITH METROPOLIS-TYPE TRANSITION RATES, Pure and Applied Analysis, vol. 3 no. 4 (January, 2021), pp. 595-612 [doi] [abs] .
  73. Ding, Z; Li, Q; Lu, J; Wright, SJ, Random Coordinate Underdamped Langevin Monte Carlo, Proceedings of Machine Learning Research, vol. 130 (January, 2021), pp. 2701-2709 [abs] .
  74. Ding, Z; Li, Q; Lu, J; Wright, SJ, Random Coordinate Underdamped Langevin Monte Carlo, 24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS), vol. 130 (2021), pp. 2701-2709 [abs] .
  75. Li, L; Goodrich, C; Yang, H; Phillips, KR; Jia, Z; Chen, H; Wang, L; Zhong, J; Liu, A; Lu, J; Shuai, J; Brenner, MP; Spaepen, F; Aizenberg, J, Microscopic origins of the crystallographically preferred growth in evaporation-induced colloidal crystals, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 118 no. 32 (2021) [doi] .
  76. Lu, J; Wang, L, Complexity of zigzag sampling algorithm for strongly log-concave distributions, Stat Comput, vol. 32 (December, 2020), pp. 48 [abs] .
  77. Han, J; Lu, J; Zhou, M, Solving high-dimensional eigenvalue problems using deep neural networks: A diffusion Monte Carlo like approach, Journal of Computational Physics, vol. 423 (December, 2020) [doi] [abs] .
  78. Lu, J; Lu, Y; Zhou, Z, Continuum limit and preconditioned Langevin sampling of the path integral molecular dynamics, Journal of Computational Physics, vol. 423 (December, 2020) [doi] [abs] .
  79. Lu, J; Steinerberger, S, Neural Collapse with Cross-Entropy Loss (December, 2020) [abs] .
  80. Sen, D; Sachs, M; Lu, J; Dunson, DB, Efficient posterior sampling for high-dimensional imbalanced logistic regression., Biometrika, vol. 107 no. 4 (December, 2020), pp. 1005-1012, Oxford University Press (OUP) [doi] [abs] .
  81. Cai, Z; Lu, J; Yang, S, Inchworm Monte Carlo Method for Open Quantum Systems, Communications on Pure and Applied Mathematics, vol. 73 no. 11 (November, 2020), pp. 2430-2472 [doi] [abs] .
  82. Yu, VWZ; Campos, C; Dawson, W; García, A; Havu, V; Hourahine, B; Huhn, WP; Jacquelin, M; Jia, W; Keçeli, M; Laasner, R; Li, Y; Lin, L; Lu, J; Moussa, J; Roman, JE; Vázquez-Mayagoitia, Á; Yang, C; Blum, V, ELSI — An open infrastructure for electronic structure solvers, Computer Physics Communications, vol. 256 (November, 2020), pp. 107459-107459, Elsevier BV [doi] [abs] .
  83. Lu, J; Steinerberger, S, Synchronization of Kuramoto oscillators in dense networks, Nonlinearity, vol. 33 no. 11 (November, 2020), pp. 5905-5918 [doi] [abs] .
  84. Li, Y; Cheng, X; Lu, J, Butterfly-net: Optimal function representation based on convolutional neural networks, Communications in Computational Physics, vol. 28 no. 5 (November, 2020), pp. 1838-1885, Global Science Press [doi] [abs] .
  85. Chen, S; Li, Q; Lu, J; Wright, SJ, Manifold Learning and Nonlinear Homogenization (November, 2020) [abs] .
  86. Agazzi, A; Lu, J, Global optimality of softmax policy gradient with single hidden layer neural networks in the mean-field regime, vol. abs/2010.11858 (October, 2020), OpenReview.net [abs] .
  87. Ding, Z; Li, Q; Lu, J; Wright, SJ, Random Coordinate Langevin Monte Carlo (October, 2020) [abs] .
  88. Li, Y; Lu, J, Optimal Orbital Selection for Full Configuration Interaction (OptOrbFCI): Pursuing the Basis Set Limit under a Budget., Journal of chemical theory and computation, vol. 16 no. 10 (October, 2020), pp. 6207-6221 [doi] [abs] .
  89. Ge, R; Lee, H; Lu, J; Risteski, A, Efficient sampling from the Bingham distribution, Algorithmic Learning Theory. PMLR, 2021 (September, 2020) [abs] .
  90. Li, W; Lu, J; Wang, L, Fisher information regularization schemes for Wasserstein gradient flows, Journal of Computational Physics, vol. 416 (September, 2020) [doi] [abs] .
  91. Gao, Y; Liu, JG; Lu, J; Marzuola, JL, Analysis of a continuum theory for broken bond crystal surface models with evaporation and deposition effects, Nonlinearity, vol. 33 no. 8 (August, 2020), pp. 3816-3845 [doi] [abs] .
  92. Lu, J; Wang, L, On explicit $L^2$-convergence rate estimate for piecewise deterministic Markov processes in MCMC algorithms, Ann. Appl. Probab. 32(2): 1333-1361 (April 2022) (July, 2020) [abs] .
  93. Craig, K; Liu, J-G; Lu, J; Marzuola, JL; Wang, L, A Proximal-Gradient Algorithm for Crystal Surface Evolution (June, 2020) [abs] .
  94. Lu, J; Marzuola, JL; Watson, AB, Defect resonances of truncated crystal structures, SIAM J. Appl. Math 82, vol. 1 (June, 2020), pp. 49-74 [abs] .
  95. Cai, Z; Lu, J; Yang, S, Numerical analysis for inchworm Monte Carlo method: Sign problem and error growth (June, 2020) [abs] .
  96. Ge, R; Lee, H; Lu, J, Estimating normalizing constants for log-concave distributions: Algorithms and lower bounds, Proceedings of the Annual ACM Symposium on Theory of Computing (June, 2020), pp. 579-586 [doi] [abs] .
  97. Nishimura, A; Dunson, DB; Lu, J, Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods, Biometrika, vol. 107 no. 2 (June, 2020), pp. 365-380 [doi] [abs] .
  98. Li, Y; Lu, J; Mao, A, Variational training of neural network approximations of solution maps for physical models, Journal of Computational Physics, vol. 409 (May, 2020), pp. 109338-109338, Elsevier BV [doi] [abs] .
  99. Sachs, M; Sen, D; Lu, J; Dunson, D, Posterior computation with the Gibbs zig-zag sampler (April, 2020) [abs] .
  100. Gao, Y; Katsevich, AE; Liu, J-G; Lu, J; Marzuola, JL, Analysis of a fourth order exponential PDE arising from a crystal surface jump process with Metropolis-type transition rates, Pure Appl. Analysis, vol. 3 (March, 2020), pp. 595-612 [abs] .
  101. Lu, J; Stubbs, KD; Watson, AB, Existence and computation of generalized Wannier functions for non-periodic systems in two dimensions and higher, Arch. Rational Mech. Anal. 243, vol. 3 (March, 2020), pp. 1269-1323 [abs] .
  102. Ding, Z; Li, Q; Lu, J, Ensemble Kalman Inversion for nonlinear problems: weights, consistency, and variance bounds (March, 2020) [abs] .
  103. Lu, J; Sachs, M; Steinerberger, S, Quadrature Points via Heat Kernel Repulsion, Constructive Approximation, vol. 51 no. 1 (February, 2020), pp. 27-48 [doi] [abs] .
  104. Kovalsky, SZ; Aigerman, N; Daubechies, I; Kazhdan, M; Lu, J; Steinerberger, S, Non-Convex Planar Harmonic Maps (January, 2020) [abs] .
  105. Lu, J; Steinerberger, S, A dimension-free hermite-hadamard inequality via gradient estimates for the torsion function, Proceedings of the American Mathematical Society, vol. 148 no. 2 (January, 2020), pp. 673-679 [doi] [abs] .
  106. Chen, K; Li, Q; Lu, J; Wright, SJ, Randomized sampling for basis function construction in generalized finite element methods, Multiscale Modeling and Simulation, vol. 18 no. 2 (January, 2020), pp. 1153-1177, Society for Industrial & Applied Mathematics (SIAM) [doi] [abs] .
  107. Lu, J; Wang, Z, The full configuration interaction quantum monte carlo method through the lens of inexact power iteration, SIAM Journal on Scientific Computing, vol. 42 no. 1 (January, 2020), pp. B1-B29 [doi] [abs] .
  108. Li, L; Li, Y; Liu, JG; Liu, Z; Lu, J, A stochastic version of stein variational gradient descent for efficient sampling, Communications in Applied Mathematics and Computational Science, vol. 15 no. 1 (January, 2020), pp. 37-63, Mathematical Sciences Publishers [doi] [abs] .
  109. Lu, J; Watson, AB; Weinstein, MI, Dirac operators and domain walls, SIAM Journal on Mathematical Analysis, vol. 52 no. 2 (January, 2020), pp. 1115-1145 [doi] [abs] .
  110. CHEN, Z; LI, Y; LU, J, Tensor ring decomposition: Optimization landscape and one-loop convergence of alternating least squares, SIAM Journal on Matrix Analysis and Applications, vol. 41 no. 3 (January, 2020), pp. 1416-1442, Society for Industrial & Applied Mathematics (SIAM) [doi] [abs] .
  111. Chen, K; Li, Q; Lu, J; Wright, SJ, Random sampling and efficient algorithms for multiscale pdes, SIAM Journal on Scientific Computing, vol. 42 no. 5 (January, 2020), pp. A2974-A3005 [doi] [abs] .
  112. An, J; Lu, J; Ying, L, Stochastic modified equations for the asynchronous stochastic gradient descent, Information and Inference, vol. 9 no. 4 (January, 2020), pp. 851-873 [doi] [abs] .
  113. Lu, Y; Ma, C; Lu, J; Ying, L, A mean-field analysis of deep resnet and beyond: Towards provable optimization via overparameterization from depth, 37th International Conference on Machine Learning, ICML 2020, vol. PartF168147-9 (January, 2020), pp. 6382-6392 [abs] .
  114. Lu, Y; Lu, J, A universal approximation theorem of deep neural networks for expressing probability distributions, Advances in Neural Information Processing Systems, vol. 2020-December (January, 2020) [abs] .
  115. Han, J; Li, Y; Lin, L; Lu, J; Zhang, J; Zhang, L, Universal approximation of symmetric and anti-symmetric functions (December, 2019) [abs] .
  116. Chen, H; Li, Q; Lu, J, A numerical method for coupling the BGK model and Euler equations through the linearized Knudsen layer, Journal of Computational Physics, vol. 398 (December, 2019) [doi] [abs] .
  117. Lu, J; Sogge, CD; Steinerberger, S, Approximating pointwise products of Laplacian eigenfunctions, Journal of Functional Analysis, vol. 277 no. 9 (November, 2019), pp. 3271-3282 [doi] [abs] .
  118. Cao, Y; Lu, J; Lu, Y, Exponential Decay of Rényi Divergence Under Fokker–Planck Equations, Journal of Statistical Physics, vol. 176 no. 5 (September, 2019), pp. 1172-1184 [doi] [abs] .
  119. Cao, Y; Lu, J; Wang, L, On explicit $L^2$-convergence rate estimate for underdamped Langevin dynamics, Arch Rational Mech Anal, vol. 247 (August, 2019), pp. 90 [abs] .
  120. Wang, Z; Li, Y; Lu, J, Coordinate Descent Full Configuration Interaction., Journal of chemical theory and computation, vol. 15 no. 6 (June, 2019), pp. 3558-3569 [doi] [abs] .
  121. Liu, JG; Lu, J; Margetis, D; Marzuola, JL, Asymmetry in crystal facet dynamics of homoepitaxy by a continuum model, Physica D: Nonlinear Phenomena, vol. 393 (June, 2019), pp. 54-67 [doi] [abs] .
  122. Agazzi, A; Lu, J, Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes, PMLR, vol. 145 (May, 2019), pp. 37-74 [abs] .
  123. Lu, Y; Lu, J; Nolen, J, Accelerating Langevin Sampling with Birth-death (May, 2019) [abs] .
  124. Cao, Y; Lu, J; Lu, Y, Gradient flow structure and exponential decay of the sandwiched Rényi divergence for primitive Lindblad equations with GNS-detailed balance, Journal of Mathematical Physics, vol. 60 no. 5 (May, 2019), pp. 052202-052202, AIP Publishing [doi] [abs] .
  125. Lin, L; Lu, J; Ying, L, Numerical methods for Kohn-Sham density functional theory, Acta Numerica, vol. 28 (May, 2019), pp. 405-539 [doi] [abs] .
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