4 citations · 6 across the 6 of their papers we have counts for
7 papers
Infinite-dimensional Dyson Brownian motion(s)
Theodoros Assiotis, Fengyi Li
We study infinite-dimensional Dyson Brownian motions obtained as limits of finite systems without rescaling the actual stochastic dynamics. For , we construct determinantal pr…
Generative Modeling through Koopman Spectral Analysis: An Operator-Theoretic Perspective
Yuanchao Xu, Fengyi Li, Masahiro Fujisawa +3
We propose Koopman Spectral Wasserstein Gradient Descent (KSWGD), a particle-based generative modeling framework that learns the Langevin generator via Koopman theory and integrate…
Expected information gain estimation via density approximations: Sample allocation and dimension reduction
Fengyi Li, Ricardo Baptista, Youssef Marzouk
Computing expected information gain (EIG) from prior to posterior (equivalently, mutual information between candidate observations and model parameters or other quantities of inter…
Sharp detection of low-dimensional structure in probability measures via dimensional logarithmic Sobolev inequalities
Matthew T. C. Li, Tiangang Cui, Fengyi Li +2
Identifying low-dimensional structure in high-dimensional probability measures is an essential pre-processing step for efficient sampling. We introduce a method for identifying and…
Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities
Fengyi Li, Ayoub Belhadji, Youssef Marzouk
We study the problem of selecting experiments from a larger candidate pool, where the goal is to maximize mutual information (MI) between the selected subset and the underlying…
Stable generative modeling using Schrödinger bridges
Georg A. Gottwald, Fengyi Li, Youssef Marzouk +1
We consider the problem of sampling from an unknown distribution for which only a sufficiently large number of training samples are available. Such settings have recently drawn con…
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
Ricardo Baptista, Lianghao Cao, Joshua Chen +4
We consider the Bayesian calibration of models describing the phenomenon of block copolymer (BCP) self-assembly using image data produced by microscopy or X-ray scattering techniqu…