activity
20242026
most citedCompositional Generative Inverse Design

2 citations · 3 across the 10 of their papers we have counts for

collaborators

10 papers

stat.ML2026

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…

cs.AI2026

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…

cond-mat.dis-nn2026

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…

cs.LG2026

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…

cs.LG2025

From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control

Peiyan Hu, Xiaowei Qian, Wenhao Deng +8

The application of deep learning for partial differential equation (PDE)-constrained control is gaining increasing attention. However, existing methods rarely consider safety requi…

cs.LG2025★ 1 cited

VFScale: Intrinsic Reasoning through Verifier-Free Test-time Scalable Diffusion Model

Tao Zhang, Jia-Shu Pan, Ruiqi Feng +1

Inspired by human SYSTEM 2 thinking, LLMs excel at complex reasoning tasks via extended Chain-of-Thought. However, similar test-time scaling for diffusion models to tackle complex…

cs.LG2024

Wavelet Diffusion Neural Operator

Peiyan Hu, Rui Wang, Xiang Zheng +7

Simulating and controlling physical systems described by partial differential equations (PDEs) are crucial tasks across science and engineering. Recently, diffusion generative mode…

eess.SY2024

CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical Systems

Long Wei, Haodong Feng, Yuchen Yang +6

The control problems of complex physical systems have broad applications in science and engineering. Previous studies have shown that generative control methods based on diffusion…

cs.LG2024

DiffPhyCon: A Generative Approach to Control Complex Physical Systems

Long Wei, Peiyan Hu, Ruiqi Feng +7

Controlling the evolution of complex physical systems is a fundamental task across science and engineering. Classical techniques suffer from limited applicability or huge computati…

cs.LG2024★ 2 cited

Compositional Generative Inverse Design

Tailin Wu, Takashi Maruyama, Long Wei +4

Inverse design, where we seek to design input variables in order to optimize an underlying objective function, is an important problem that arises across fields such as mechanical…