44 citations · 117 across the 31 of their papers we have counts for
5 papers · 1 filter
Provable Probabilistic Imaging using Score-Based Generative Priors
Yu Sun, Zihui Wu, Yifan Chen +2
Estimating high-quality images while also quantifying their uncertainty are two desired features in an image reconstruction algorithm for solving ill-posed inverse problems. In thi…
Sampling via Gradient Flows in the Space of Probability Measures
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang +2
Sampling a target probability distribution with an unknown normalization constant is a fundamental challenge in computational science and engineering. Recent work shows that algori…
Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs
Pau Batlle, Yifan Chen, Bamdad Hosseini +2
We introduce a priori Sobolev-space error estimates for the solution of nonlinear, and possibly parametric, PDEs using Gaussian process and kernel based methods. The primary assump…
Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes
Yifan Chen, Houman Owhadi, Florian Schäfer
In recent years, there has been widespread adoption of machine learning-based approaches to automate the solving of partial differential equations (PDEs). Among these approaches, G…
Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance
Yifan Chen, Daniel Zhengyu Huang, Jiaoyang Huang +2
Sampling a probability distribution with an unknown normalization constant is a fundamental problem in computational science and engineering. This task may be cast as an optimizati…