4 papers · 1 filter
One step further with Monte-Carlo sampler to guide diffusion better
Minsi Ren, Wenhao Deng, Ruiqi Feng +1
Stochastic differential equation (SDE)-based generative models have achieved substantial progress in conditional generation via training-free differentiable loss-guided approaches.…
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…
Unlocking Reasoning Capabilities in LLMs via Reinforcement Learning Exploration
Wenhao Deng, Long Wei, Chenglei Yu +1
Reinforcement learning with verifiable rewards (RLVR) has recently enhanced the reasoning capabilities of large language models (LLMs), particularly for mathematical problem solvin…
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…