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Haoxuan Chen
Haoxuan Chen
PhD Candidate at ICME, Stanford University
Verificeret mail på stanford.edu - Startside
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Physics-informed neural operator for learning partial differential equations
Z Li, H Zheng, N Kovachki, D Jin, H Chen, B Liu, K Azizzadenesheli, ...
ACM/JMS Journal of Data Science 1 (3), 1-27, 2024
5032024
Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality
Y Lu, H Chen, J Lu, L Ying, J Blanchet
The Tenth International Conference on Learning Representations, 2022
552022
Accelerating diffusion models with parallel sampling: Inference at sub-linear time complexity
H Chen, Y Ren, L Ying, G Rotskoff
Advances in Neural Information Processing Systems 37, 133661-133709, 2025
92025
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
Y Ren, H Chen, GM Rotskoff, L Ying
The Thirteenth International Conference on Learning Representations, 2025
72025
When can regression-adjusted control variate help? rare events, sobolev embedding and minimax optimality
J Blanchet, H Chen, Y Lu, L Ying
Advances in Neural Information Processing Systems 36, 36566-36578, 2023
42023
Ensemble-Based Annealed Importance Sampling
H Chen, L Ying
arXiv preprint arXiv:2401.15645, 2024
32024
Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms
Y Ren*, H Chen*, Y Zhu*, W Guo*, Y Chen, GM Rotskoff, M Tao, L Ying
arXiv preprint arXiv:2502.00234, 2025
12025
Approximation of High-Dimensional Gibbs Distributions with Functional Hierarchical Tensors
N Sheng, X Tang, H Chen, L Ying
arXiv preprint arXiv:2501.17143, 2025
2025
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Artikler 1–8