The method of polarized traces for the 2D Helmholtz equation. - Leonardo Zepeda-Núñez; Laurent Demanet (J. Comput. Phys., 2016)

Fast Alternating BiDirectional Preconditioner for the 2D High-Frequency Lippmann-Schwinger Equation. - Leonardo Zepeda-Núñez; Hongkai Zhao (SIAM J. Sci. Comput., 2016)

A hybrid approach to solve the high-frequency Helmholtz equation with source singularity in smooth heterogeneous media. - Jun Fang 004; Jianliang Qian; Leonardo Zepeda-Núñez; Hongkai Zhao (J. Comput. Phys., 2018)

Nested Domain Decomposition with Polarized Traces for the 2D Helmholtz Equation. - Leonardo Zepeda-Núñez; Laurent Demanet (SIAM J. Sci. Comput., 2018)

A Multiscale Neural Network Based on Hierarchical Matrices. - Yuwei Fan; Lin Lin 001; Lexing Ying; Leonardo Zepeda-Núñez (Multiscale Model. Simul., 2019)

Projection-Based Embedding Theory for Solving Kohn-Sham Density Functional Theory. - Lin Lin 001; Leonardo Zepeda-Núñez (Multiscale Model. Simul., 2019)

Learning the mapping $ mathbf{x} mapsto sum_{i=1}^d x_i^2$: the cost of finding the needle in a haystack. - Jiefu Zhang; Leonardo Zepeda-Núñez; Yuan Yao; Lin Lin 001 (CoRR, 2020)

L-Sweeps: A scalable, parallel preconditioner for the high-frequency Helmholtz equation. - Matthias Taus; Leonardo Zepeda-Núñez; Russell J. Hewett; Laurent Demanet (J. Comput. Phys., 2020)

Bridging and Improving Theoretical and Computational Electric Impedance Tomography via Data Completion. - Tan Bui-Thanh; Qin Li 007; Leonardo Zepeda-Núñez (CoRR, 2021)

Accurate and Robust Deep Learning Framework for Solving Wave-Based Inverse Problems in the Super-Resolution Regime. - Matthew Li; Laurent Demanet; Leonardo Zepeda-Núñez (CoRR, 2021)

Deep Density: Circumventing the Kohn-Sham equations via symmetry preserving neural networks. - Leonardo Zepeda-Núñez; Yixiao Chen; Jiefu Zhang; Weile Jia; Linfeng Zhang 002; Lin Lin 001 (J. Comput. Phys., 2021)

Solving the Wide-band Inverse Scattering Problem via Equivariant Neural Networks. - Borong Zhang; Leonardo Zepeda-Núñez; Qin Li 007 (CoRR, 2022)

Bridging and Improving Theoretical and Computational Electrical Impedance Tomography via Data Completion. - Tan Bui-Thanh; Qin Li 007; Leonardo Zepeda-Núñez (SIAM J. Sci. Comput., 2022)

Wide-Band Butterfly Network: Stable and Efficient Inversion Via Multi-Frequency Neural Networks. - Matthew Li; Laurent Demanet; Leonardo Zepeda-Núñez (Multiscale Model. Simul., 2022)

Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems. - Zhong Yi Wan; Leonardo Zepeda-Núñez; Anudhyan Boral; Fei Sha (ICLR, 2023)

User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. - Marc Anton Finzi; Anudhyan Boral; Andrew Gordon Wilson; Fei Sha; Leonardo Zepeda-Núñez (ICML, 2023)

Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. - Anudhyan Boral; Zhong Yi Wan; Leonardo Zepeda-Núñez; James Lottes; Qing Wang 032; Yi-Fan Chen; John Anderson; Fei Sha (NeurIPS, 2023)

Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models. - Zhong Yi Wan; Ricardo Baptista; Anudhyan Boral; Yi-Fan Chen; John Anderson; Fei Sha; Leonardo Zepeda-Núñez (NeurIPS, 2023)

Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. - Anudhyan Boral; Zhong Yi Wan; Leonardo Zepeda-Núñez; James Lottes; Qing Wang 032; Yi-Fan Chen; John Robert Anderson; Fei Sha (CoRR, 2023)

Efficient long-range convolutions for point clouds. - Yifan Peng 005; Lin Lin 001; Lexing Ying; Leonardo Zepeda-Núñez (J. Comput. Phys., 2023)

Learning to correct spectral methods for simulating turbulent flows. - Gideon Dresdner; Dmitrii Kochkov; Peter Christian Norgaard; Leonardo Zepeda-Núñez; Jamie A. Smith; Michael P. Brenner; Stephan Hoyer (Trans. Mach. Learn. Res., 2023)

High-Frequency Limit of the Inverse Scattering Problem: Asymptotic Convergence from Inverse Helmholtz to Inverse Liouville. - Shi Chen 003; Zhiyan Ding; Qin Li 007; Leonardo Zepeda-Núñez (SIAM J. Imaging Sci., 2023)

DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. - Yair Schiff; Zhong Yi Wan; Jeffrey B. Parker; Stephan Hoyer; Volodymyr Kuleshov; Fei Sha; Leonardo Zepeda-Núñez (ICML, 2024)

A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data. - Benedikt Barthel Sorensen; Leonardo Zepeda-Núñez; Ignacio Lopez-Gomez; Zhong Yi Wan; Rob Carver; Fei Sha; Themistoklis P. Sapsis (CoRR, 2024)

Back-Projection Diffusion: Solving the Wideband Inverse Scattering Problem with Diffusion Models. - Borong Zhang; Martin Guerra; Qin Li 007; Leonardo Zepeda-Núñez (CoRR, 2024)

Rational-WENO: A lightweight, physically-consistent three-point weighted essentially non-oscillatory scheme. - Shantanu Shahane; Sheide Chammas; Deniz A. Bezgin; Aaron B. Buhendwa; Steffen J. Schmidt; Nikolaus A. Adams; Spencer H. Bryngelson; Yi-Fan Chen; Qing Wang 032; Fei Sha; Leonardo Zepeda-Núñez (CoRR, 2024)

Generative AI for fast and accurate Statistical Computation of Fluids. - Roberto Molinaro; Samuel Lanthaler; Bogdan Raonic; Tobias Rohner; Victor Armegioiu; Zhong Yi Wan; Fei Sha; Siddhartha Mishra; Leonardo Zepeda-Núñez (CoRR, 2024)

Dynamical-generative downscaling of climate model ensembles. - Ignacio Lopez-Gomez; Zhong Yi Wan; Leonardo Zepeda-Núñez; Tapio Schneider; John R. Anderson; Fei Sha (CoRR, 2024)

Statistical Downscaling via High-Dimensional Distribution Matching with Generative Models. - Zhong Yi Wan; Ignacio Lopez-Gomez; Rob Carver; Tapio Schneider; John R. Anderson; Fei Sha; Leonardo Zepeda-Núñez (CoRR, 2024)

Solving the wide-band inverse scattering problem via equivariant neural networks. - Borong Zhang; Leonardo Zepeda-Núñez; Qin Li (J. Comput. Appl. Math., 2024)