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03/27/2023
Text-to-Image Diffusion Models are Zero-Shot Classifiers
The excellent generative capabilities of text-to-image diffusion models ...
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11/26/2021
Particle Dynamics for Learning EBMs
Energy-based modeling is a promising approach to unsupervised learning, ...
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06/15/2021
Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent
We focus on the problem of efficient sampling and learning of probabilit...
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02/10/2021
Argmax Flows and Multinomial Diffusion: Towards Non-Autoregressive Language Models
The field of language modelling has been largely dominated by autoregres...
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02/04/2021
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC
Hybrid Monte Carlo is a powerful Markov Chain Monte Carlo method for sam...
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11/14/2020
Self Normalizing Flows
Efficient gradient computation of the Jacobian determinant term is a cor...
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07/06/2020
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
Normalizing flows and variational autoencoders are powerful generative m...
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03/08/2020
Complete Hierarchy of Relaxation for Constrained Signomial Positivity
In this article, we prove that the Sums-of-AM/GM Exponential (SAGE) rela...
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07/10/2019
Tails of Triangular Flows
Triangular maps are a construct in probability theory that allows the tr...
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05/07/2019
Sum-of-Squares Polynomial Flow
Triangular map is a recent construct in probability theory that allows o...
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09/19/2016