Francisco J. R. Ruiz | DeepAI

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Featured Co-authors

Arnaud Doucet
106 publications
Xu Han
93 publications
David M. Blei
92 publications
Stephan Mandt
62 publications
Susan Athey
41 publications
Fernando Perez-Cruz
35 publications
Lennart Svensson
33 publications
Xiaohui Chen
32 publications
Michalis K. Titsias
31 publications
Isabel Valera
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Ömer Deniz Akyıldız
19 publications

∙ 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...

0 Xiaohui Chen, et al. ∙

∙ 10/20/2020

VarGrad: A Low-Variance Gradient Estimator for Variational Inference

We analyse the properties of an unbiased gradient estimator of the ELBO ...

0 Lorenz Richter, et al. ∙

∙ 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 ...

9 Francisco J. R. Ruiz, et al. ∙

∙ 10/09/2019

Prescribed Generative Adversarial Networks

Generative adversarial networks (GANs) are a powerful approach to unsupe...

25 Adji B. Dieng, et al. ∙

∙ 07/12/2019

The Dynamic Embedded Topic Model

Topic modeling analyzes documents to learn meaningful patterns of words....

0 Adji B. Dieng, et al. ∙

∙ 07/08/2019

Topic Modeling in Embedding Spaces

Topic modeling analyzes documents to learn meaningful patterns of words....

2 Adji B. Dieng, et al. ∙

∙ 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...

0 Francisco J. R. Ruiz, et al. ∙

∙ 11/07/2018

Poisson Multi-Bernoulli Mapping Using Gibbs Sampling

This paper addresses the mapping problem. Using a conjugate prior form, ...

0 Maryam Fatemi, et al. ∙

∙ 10/18/2018

Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation

New communication standards need to deal with machine-to-machine communi...

0 Francisco J. R. Ruiz, et al. ∙

∙ 08/06/2018

Unbiased Implicit Variational Inference

We develop unbiased implicit variational inference (UIVI), a method that...

0 Michalis K. Titsias, et al. ∙

∙ 02/12/2018

Augment and Reduce: Stochastic Inference for Large Categorical Distributions

Categorical distributions are ubiquitous in machine learning, e.g., in c...

0 Francisco J. R. Ruiz, et al. ∙

∙ 11/09/2017

SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements

We develop SHOPPER, a sequential probabilistic model of market baskets. ...

0 Francisco J. R. Ruiz, et al. ∙

∙ 10/18/2016

Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms

Variational inference using the reparameterization trick has enabled lar...

0 Christian A. Naesseth, et al. ∙

∙ 10/07/2016

The Generalized Reparameterization Gradient

The reparameterization gradient has become a widely used method to obtai...

0 Francisco J. R. Ruiz, et al. ∙

∙ 08/02/2016

Exponential Family Embeddings

Word embeddings are a powerful approach for capturing semantic similarit...

0 Maja R. Rudolph, et al. ∙

∙ 03/03/2016

Overdispersed Black-Box Variational Inference

We introduce overdispersed black-box variational inference, a method to ...

0 Francisco J. R. Ruiz, et al. ∙

∙ 01/29/2014

Bayesian nonparametric comorbidity analysis of psychiatric disorders

The analysis of comorbidity is an open and complex research field in the...

0 Francisco J. R. Ruiz, et al. ∙

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