Search Results for author: Michael Lindsey

Found 4 papers, 0 papers with code

Multimarginal generative modeling with stochastic interpolants

no code implementations5 Oct 2023 Michael S. Albergo, Nicholas M. Boffi, Michael Lindsey, Eric Vanden-Eijnden

Given a set of $K$ probability densities, we consider the multimarginal generative modeling problem of learning a joint distribution that recovers these densities as marginals.

Fairness Style Transfer

Tensorizing flows: a tool for variational inference

no code implementations3 May 2023 Yuehaw Khoo, Michael Lindsey, Hongli Zhao

Fueled by the expressive power of deep neural networks, normalizing flows have achieved spectacular success in generative modeling, or learning to draw new samples from a distribution given a finite dataset of training samples.

Tensor Networks Variational Inference

Understanding and eliminating spurious modes in variational Monte Carlo using collective variables

no code implementations11 Nov 2022 huan zhang, Robert J. Webber, Michael Lindsey, Timothy C. Berkelbach, Jonathan Weare

The use of neural network parametrizations to represent the ground state in variational Monte Carlo (VMC) calculations has generated intense interest in recent years.

Variational Monte Carlo

Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo

no code implementations19 Jun 2021 Robert J. Webber, Michael Lindsey

Second, in order to realize this favorable comparison in the presence of stochastic noise, we analyze the effect of sampling error on VMC parameter updates and experimentally demonstrate that it can be reduced by the parallel tempering method.

Variational Monte Carlo

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