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04/13/2023
Sample Average Approximation for Black-Box VI
We present a novel approach for black-box VI that bypasses the difficult...
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02/27/2023
U-Statistics for Importance-Weighted Variational Inference
We propose the use of U-statistics to reduce variance for gradient estim...
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02/01/2023
Automatically Marginalized MCMC in Probabilistic Programming
Hamiltonian Monte Carlo (HMC) is a powerful algorithm to sample latent v...
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03/25/2019
The Random Conditional Distribution for Higher-Order Probabilistic Inference
The need to condition distributional properties such as expectation, var...
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01/16/2019
Soft Constraints for Inference with Declarative Knowledge
We develop a likelihood free inference procedure for conditioning a prob...
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09/30/2018
Extending Stan for Deep Probabilistic Programming
Deep probabilistic programming combines deep neural networks (for automa...
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08/01/2018
Inference of Users Demographic Attributes based on Homophily in Communication Networks
Over the past decade, mobile phones have become prevalent in all parts o...
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06/14/2010
Outrepasser les limites des techniques classiques de Prise d'Empreintes grace aux Reseaux de Neurones
We present an application of Artificial Intelligence techniques to the f...
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06/09/2010