3 citations · 8 across the 16 of their papers we have counts for
5 papers · 1 filter
On the design of scalable, high-precision spherical-radial Fourier features
Ayoub Belhadji, Qianyu Julie Zhu, Youssef Marzouk
Approximation using Fourier features is a popular technique for scaling kernel methods to large-scale problems, with myriad applications in machine learning and statistics. This me…
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…
Sampling in Unit Time with Kernel Fisher-Rao Flow
Aimee Maurais, Youssef Marzouk
We introduce a new mean-field ODE and corresponding interacting particle systems (IPS) for sampling from an unnormalized target density. The IPS are gradient-free, available in clo…