7 papers
FES-FM: Free Energy Surface Sampling via Reduced Flow Matching
Zichen Liu, Tiejun Li
Sampling the distribution of collective variables (CVs) and estimating the associated free energy surface are crucial problems in statistical physics, as they underpin a better und…
WFR-FM: Simulation-Free Dynamic Unbalanced Optimal Transport
Qiangwei Peng, Zihan Wang, Junda Ying +5
The Wasserstein-Fisher-Rao (WFR) metric extends dynamic optimal transport (OT) by coupling displacement with change of mass, providing a principled geometry for modeling unbalanced…
WFR-MFM: One-Step Inference for Dynamic Unbalanced Optimal Transport
Xinyu Wang, Ruoyu Wang, Qiangwei Peng +2
Reconstructing dynamical evolution from limited observations is a fundamental challenge in single-cell biology, where dynamic unbalanced optimal transport provides a principled fra…
Variational Regularized Unbalanced Optimal Transport: Single Network, Least Action
Yuhao Sun, Zhenyi Zhang, Zihan Wang +2
Recovering the dynamics from a few snapshots of a high-dimensional system is a challenging task in statistical physics and machine learning, with important applications in computat…
Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schrödinger Bridge
Zhenyi Zhang, Zihan Wang, Yuhao Sun +2
Modeling the dynamics from sparsely time-resolved snapshot data is crucial for understanding complex cellular processes and behavior. Existing methods leverage optimal transport, S…
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport
Zhenyi Zhang, Tiejun Li, Peijie Zhou
Reconstructing dynamics using samples from sparsely time-resolved snapshots is an important problem in both natural sciences and machine learning. Here, we introduce a new deep lea…