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06/11/2021
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
A graph generative model defines a distribution over graphs. One type of...
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10/20/2020
VarGrad: A Low-Variance Gradient Estimator for Variational Inference
We analyse the properties of an unbiased gradient estimator of the ELBO ...
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10/05/2020
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains
The variational auto-encoder (VAE) is a deep latent variable model that ...
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10/09/2019
Prescribed Generative Adversarial Networks
Generative adversarial networks (GANs) are a powerful approach to unsupe...
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07/12/2019
The Dynamic Embedded Topic Model
Topic modeling analyzes documents to learn meaningful patterns of words....
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07/08/2019
Topic Modeling in Embedding Spaces
Topic modeling analyzes documents to learn meaningful patterns of words....
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05/10/2019
A Contrastive Divergence for Combining Variational Inference and MCMC
We develop a method to combine Markov chain Monte Carlo (MCMC) and varia...
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11/07/2018
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling
This paper addresses the mapping problem. Using a conjugate prior form, ...
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10/18/2018
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation
New communication standards need to deal with machine-to-machine communi...
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08/06/2018
Unbiased Implicit Variational Inference
We develop unbiased implicit variational inference (UIVI), a method that...
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02/12/2018
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
Categorical distributions are ubiquitous in machine learning, e.g., in c...
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11/09/2017
SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements
We develop SHOPPER, a sequential probabilistic model of market baskets. ...
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10/18/2016
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms
Variational inference using the reparameterization trick has enabled lar...
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10/07/2016
The Generalized Reparameterization Gradient
The reparameterization gradient has become a widely used method to obtai...
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08/02/2016
Exponential Family Embeddings
Word embeddings are a powerful approach for capturing semantic similarit...
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03/03/2016
Overdispersed Black-Box Variational Inference
We introduce overdispersed black-box variational inference, a method to ...
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01/29/2014