16 papers
Rare Event Analysis via Stochastic Optimal Control
Yuanqi Du, Jiajun He, Dinghuai Zhang +2
Rare events such as conformational changes in biomolecules, phase transitions, and chemical reactions are central to the behavior of many physical systems, yet they are extremely d…
Towards Diverse Scientific Hypothesis Search with Large Language Models
Haorui Wang, Parshin Shojaee, Kazem Meidani +7
Large language models (LLMs) are on the rise for accelerating scientific discovery, most recently in advanced tasks such as generating valid scientific hypotheses. Yet in many disc…
Free energy Estimation on Any State Space
Jiajun He, Zijing Ou, Francisco Vargas +4
Free energy estimation is a fundamental yet challenging problem, from physics to statistics. Classical approaches rely on thermodynamic transformations, ranging from direct estimat…
Training-Free Vector Quantization via Gaussian VAEs
Tongda Xu, Wendi Zheng, Jiajun He +4
Vector-quantized variational autoencoders (VQ-VAEs) are discrete autoencoders that compress images into discrete tokens. However, they are difficult to train due to discretization.…
Compression as Adaptation: Implicit Visual Representation with Diffusion Foundation Models
Zongyu Guo, Jiajun He, Zhaoyang Jia +6
Modern visual generative models acquire rich visual knowledge through large-scale training, yet existing visual representations (such as pixels, latents, or tokens) remain external…
RNE: plug-and-play diffusion inference-time control and energy-based training
Jiajun He, José Miguel Hernández-Lobato, Yuanqi Du +1
Diffusion models generate data by removing noise gradually, which corresponds to the time-reversal of a noising process. However, access to only the denoising kernels is often insu…