2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Bayesian Filtering in Physical Systems via Test-time Trained Flow Matching
Ruiqi Feng, Chongyi Wang, Tao Zhang +1
Bayesian filtering provides a principled framework for online state estimation under uncertainty, yet its application to systems with high-dimensional states and complicated poster…
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…
Training cell stress patterns in 3D cellular packings
Shabeeb Ameen, Tao Zhang, J. M. Schwarz
The task of learning patterns is typically associated with systems that update parameters on fixed architectures, such as neural networks, where learning proceeds through continuou…
GenCP: Towards Generative Modeling Paradigm of Coupled Physics
Tianrun Gao, Haoren Zheng, Wenhao Deng +5
Real-world physical systems are inherently complex, often involving the coupling of multiple physics, making their simulation both highly valuable and challenging. Many mainstream…