30 citations · 39 across the 15 of their papers we have counts for
4 papers · 1 filter
Solving Inverse Problems of Chaotic Systems with Bidirectional Conditional Flow Matching
Peiyan Hu, Jian Zhang, Jiashu Pan +6
Modeling chaotic systems is crucial yet challenging. Inverse problems in chaotic dynamics, namely inferring initial conditions from final states, remain largely unsolved because of…
Wiener Chaos Expansion based Neural Operator for Singular Stochastic Partial Differential Equations
Dai Shi, Luke Thompson, Andi Han +3
In this paper, we explore how our recently developed Wiener Chaos Expansion (WCE)-based neural operator (NO) can be applied to singular stochastic partial differential equations, e…
RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data
Peiyan Hu, Haodong Feng, Hongyuan Liu +13
Predicting the evolution of complex physical systems remains a central problem in science and engineering. Despite rapid progress in scientific Machine Learning (ML) models, a crit…
On the Design of One-step Diffusion via Shortcutting Flow Paths
Haitao Lin, Peiyan Hu, Minsi Ren +5
Recent advances in few-step diffusion models have demonstrated their efficiency and effectiveness by shortcutting the probabilistic paths of diffusion models, especially in trainin…