Leonardo Zepeda-Núñez

40 papers A* 5Journal 35

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data. CoRR Benedikt Barthel Sorensen, Leonardo Zepeda-Núñez, Ignacio Lopez-Gomez, Zhong Yi Wan, Rob Carver, Fei Sha, Themistoklis P. Sapsis
2024	J	`jnl`	Back-Projection Diffusion: Solving the Wideband Inverse Scattering Problem with Diffusion Models. CoRR Borong Zhang, Martin Guerra, Qin Li, Leonardo Zepeda-Núñez
2024	A*	`conf`	DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. ICML Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez
2024	J	`jnl`	DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. CoRR Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez
2024	J	`jnl`	Dynamical-generative downscaling of climate model ensembles. CoRR Ignacio Lopez-Gomez, Zhong Yi Wan, Leonardo Zepeda-Núñez, Tapio Schneider, John R. Anderson, Fei Sha
2024	J	`jnl`	Generative AI for fast and accurate Statistical Computation of Fluids. CoRR Roberto Molinaro, Samuel Lanthaler, Bogdan Raonic, Tobias Rohner, Victor Armegioiu, Zhong Yi Wan, Fei Sha, Siddhartha Mishra, Leonardo Zepeda-Núñez
2024	J	`jnl`	Rational-WENO: A lightweight, physically-consistent three-point weighted essentially non-oscillatory scheme. CoRR Shantanu Shahane, Sheide Chammas, Deniz A. Bezgin, Aaron B. Buhendwa, Steffen J. Schmidt, Nikolaus A. Adams, Spencer H. Bryngelson, Yi-Fan Chen, Qing Wang, Fei Sha, Leonardo Zepeda-Núñez
2024	J	`jnl`	Solving the wide-band inverse scattering problem via equivariant neural networks. J. Comput. Appl. Math. Borong Zhang, Leonardo Zepeda-Núñez, Qin Li
2024	J	`jnl`	Statistical Downscaling via High-Dimensional Distribution Matching with Generative Models. CoRR Zhong Yi Wan, Ignacio Lopez-Gomez, Rob Carver, Tapio Schneider, John R. Anderson, Fei Sha, Leonardo Zepeda-Núñez
2023	A*	`conf`	Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models. NeurIPS Zhong Yi Wan, Ricardo Baptista, Anudhyan Boral, Yi-Fan Chen, John Anderson, Fei Sha, Leonardo Zepeda-Núñez
2023	J	`jnl`	Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models. CoRR Zhong Yi Wan, Ricardo Baptista, Yi-Fan Chen, John Anderson, Anudhyan Boral, Fei Sha, Leonardo Zepeda-Núñez
2023	J	`jnl`	Efficient long-range convolutions for point clouds. J. Comput. Phys. Yifan Peng, Lin Lin, Lexing Ying, Leonardo Zepeda-Núñez
2023	A*	`conf`	Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems. ICLR Zhong Yi Wan, Leonardo Zepeda-Núñez, Anudhyan Boral, Fei Sha
2023	J	`jnl`	Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems. CoRR Zhong Yi Wan, Leonardo Zepeda-Núñez, Anudhyan Boral, Fei Sha
2023	J	`jnl`	High-Frequency Limit of the Inverse Scattering Problem: Asymptotic Convergence from Inverse Helmholtz to Inverse Liouville. SIAM J. Imaging Sci. Shi Chen, Zhiyan Ding, Qin Li, Leonardo Zepeda-Núñez
2023	J	`jnl`	Learning to correct spectral methods for simulating turbulent flows. Trans. Mach. Learn. Res. Gideon Dresdner, Dmitrii Kochkov, Peter Christian Norgaard, Leonardo Zepeda-Núñez, Jamie A. Smith, Michael P. Brenner, Stephan Hoyer
2023	A*	`conf`	Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. NeurIPS Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez, James Lottes, Qing Wang, Yi-Fan Chen, John Anderson, Fei Sha
2023	J	`jnl`	Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations. CoRR Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez, James Lottes, Qing Wang, Yi-Fan Chen, John Robert Anderson, Fei Sha
2023	A*	`conf`	User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. ICML Marc Anton Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez
2023	J	`jnl`	User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. CoRR Marc Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Núñez
2022	J	`jnl`	Bridging and Improving Theoretical and Computational Electrical Impedance Tomography via Data Completion. SIAM J. Sci. Comput. Tan Bui-Thanh, Qin Li, Leonardo Zepeda-Núñez
2022	J	`jnl`	High-frequency limit of the inverse scattering problem: asymptotic convergence from inverse Helmholtz to inverse Liouville. CoRR Shi Chen, Zhiyan Ding, Qin Li, Leonardo Zepeda-Núñez
2022	J	`jnl`	Learning to correct spectral methods for simulating turbulent flows. CoRR Gideon Dresdner, Dmitrii Kochkov, Peter C. Norgaard, Leonardo Zepeda-Núñez, Jamie A. Smith, Michael P. Brenner, Stephan Hoyer
2022	J	`jnl`	Solving the Wide-band Inverse Scattering Problem via Equivariant Neural Networks. CoRR Borong Zhang, Leonardo Zepeda-Núñez, Qin Li
2022	J	`jnl`	Wide-Band Butterfly Network: Stable and Efficient Inversion Via Multi-Frequency Neural Networks. Multiscale Model. Simul. Matthew Li, Laurent Demanet, Leonardo Zepeda-Núñez
2021	J	`jnl`	Accurate and Robust Deep Learning Framework for Solving Wave-Based Inverse Problems in the Super-Resolution Regime. CoRR Matthew Li, Laurent Demanet, Leonardo Zepeda-Núñez
2021	J	`jnl`	Bridging and Improving Theoretical and Computational Electric Impedance Tomography via Data Completion. CoRR Tan Bui-Thanh, Qin Li, Leonardo Zepeda-Núñez
2021	J	`jnl`	Deep Density: Circumventing the Kohn-Sham equations via symmetry preserving neural networks. J. Comput. Phys. Leonardo Zepeda-Núñez, Yixiao Chen, Jiefu Zhang, Weile Jia, Linfeng Zhang, Lin Lin
2020	J	`jnl`	Efficient Long-Range Convolutions for Point Clouds. CoRR Yifan Peng, Lin Lin, Lexing Ying, Leonardo Zepeda-Núñez
2020	J	`jnl`	L-Sweeps: A scalable, parallel preconditioner for the high-frequency Helmholtz equation. J. Comput. Phys. Matthias Taus, Leonardo Zepeda-Núñez, Russell J. Hewett, Laurent Demanet
2020	J	`jnl`	Learning the mapping $\mathbf{x}\mapsto \sum_{i=1}^d x_i^2$: the cost of finding the needle in a haystack. CoRR Jiefu Zhang, Leonardo Zepeda-Núñez, Yuan Yao, Lin Lin
2020	J	`jnl`	Wide-band butterfly network: stable and efficient inversion via multi-frequency neural networks. CoRR Matthew Li, Laurent Demanet, Leonardo Zepeda-Núñez
2019	J	`jnl`	A Multiscale Neural Network Based on Hierarchical Matrices. Multiscale Model. Simul. Yuwei Fan, Lin Lin, Lexing Ying, Leonardo Zepeda-Núñez
2019	J	`jnl`	Deep Density: circumventing the Kohn-Sham equations via symmetry preserving neural networks. CoRR Leonardo Zepeda-Núñez, Yixiao Chen, Jiefu Zhang, Weile Jia, Linfeng Zhang, Lin Lin
2019	J	`jnl`	L-Sweeps: A scalable, parallel preconditioner for the high-frequency Helmholtz equation. CoRR Matthias Taus, Leonardo Zepeda-Núñez, Russell J. Hewett, Laurent Demanet
2019	J	`jnl`	Projection-Based Embedding Theory for Solving Kohn-Sham Density Functional Theory. Multiscale Model. Simul. Lin Lin, Leonardo Zepeda-Núñez
2018	J	`jnl`	A hybrid approach to solve the high-frequency Helmholtz equation with source singularity in smooth heterogeneous media. J. Comput. Phys. Jun Fang, Jianliang Qian, Leonardo Zepeda-Núñez, Hongkai Zhao
2018	J	`jnl`	Nested Domain Decomposition with Polarized Traces for the 2D Helmholtz Equation. SIAM J. Sci. Comput. Leonardo Zepeda-Núñez, Laurent Demanet
2016	J	`jnl`	Fast Alternating BiDirectional Preconditioner for the 2D High-Frequency Lippmann-Schwinger Equation. SIAM J. Sci. Comput. Leonardo Zepeda-Núñez, Hongkai Zhao
2016	J	`jnl`	The method of polarized traces for the 2D Helmholtz equation. J. Comput. Phys. Leonardo Zepeda-Núñez, Laurent Demanet