11 citations · 27 across the 22 of their papers we have counts for
5 papers · 1 filter
SURGE: Approximation and Training Free Particle Filter for Diffusion Surrogate
Lifu Wei, Yinuo Ren, Naichen Shi +1
Data assimilation (DA) addresses the problem of sequentially estimating the state of a dynamical system from noisy and incomplete observations. In this work, we employ a diffusion…
Simple Approximation and Derivative Free Inference-Time Scaling for Diffusion Models via Sequential Monte Carlo on Path Measures
Chenyang Wang, Weizhong Wang, Yinuo Ren +2
iffusion-based generative models increasingly rely on inference-time guidance, adding a drift term or reweighting mixture of experts, to improve sample quality on task-specific obj…
A Covering Framework for Offline POMDPs Learning using Belief Space Metric
Youheng Zhu, Yiping Lu
In off policy evaluation (OPE) for partially observable Markov decision processes (POMDPs), an agent must infer hidden states from past observations, which exacerbates both the cur…
Benign overfitting in Fixed Dimension via Physics-Informed Learning with Smooth Inductive Bias
Honam Wong, Wendao Wu, Fanghui Liu +1
Recent advances in machine learning have inspired a surge of research into reconstructing specific quantities of interest from measurements that comply with certain physical laws.…
Statistical Spatially Inhomogeneous Diffusion Inference
Yinuo Ren, Yiping Lu, Lexing Ying +1
Inferring a diffusion equation from discretely-observed measurements is a statistical challenge of significant importance in a variety of fields, from single-molecule tracking in b…