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08/28/2023
NAS-X: Neural Adaptive Smoothing via Twisting
We present Neural Adaptive Smoothing via Twisting (NAS-X), a method for ...
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10/09/2021
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?
Posterior predictive distributions quantify uncertainties ignored by poi...
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10/31/2019
Energy-Inspired Models: Learning with Sampler-Induced Distributions
Energy-based models (EBMs) are powerful probabilistic models, but suffer...
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10/09/2018
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
Deep latent variable models have become a popular model choice due to th...
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06/16/2017
An online sequence-to-sequence model for noisy speech recognition
Generative models have long been the dominant approach for speech recogn...
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05/25/2017
Filtering Variational Objectives
When used as a surrogate objective for maximum likelihood estimation in ...
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05/16/2017
Learning Hard Alignments with Variational Inference
There has recently been significant interest in hard attention models fo...
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03/21/2017
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
Learning in models with discrete latent variables is challenging due to ...
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02/24/2017
