Zhong Yi Wan

17 papers A* 4Misc 1Journal 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
Efficient, Property-Aligned Fan-Out Retrieval via RL-Compiled Diffusion.
CoRR
Pengcheng Jiang, Judith Yue Li, Moonkyung Ryu, R. Lily Hu, Kun Su, Zhong Yi Wan, Liam Hebert, Hao Peng, Jiawei Han, Dima Kuzmin, Craig Boutilier
2025 Misc conf
Diff4Steer: Steerable Diffusion Prior for Generative Music Retrieval with Semantic Guidance.
ICASSP
Xuchan Bao, Judith Yue Li, Zhong Yi Wan, Kun Su, Timo I. Denk, Joonseok Lee, Dima Kuzmin, Fei Sha
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
Diff4Steer: Steerable Diffusion Prior for Generative Music Retrieval with Semantic Guidance.
CoRR
Xuchan Bao, Judith Yue Li, Zhong Yi Wan, Kun Su, Timo I. Denk, Joonseok Lee, Dima Kuzmin, Fei Sha
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
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 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 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
2021 J jnl
A data-driven framework for the stochastic reconstruction of small-scale features with application to climate data sets.
J. Comput. Phys.
Zhong Yi Wan, Boyko A. Dodov, Christian Lessig, Henk Dijkstra, Themistoklis P. Sapsis
2018 J jnl
Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long-Short Term Memory Networks.
CoRR
Pantelis-Rafail Vlachas, Wonmin Byeon, Zhong Yi Wan, Themistoklis P. Sapsis, Petros Koumoutsakos