2 citations · 3 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
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…
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…