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BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling


Feb 06, 2019
Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther


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An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models


Oct 28, 2018
Ulrich Paquet, Marco Fraccaro

* Technical report accompanying arXiv:1604.01972, "An Adaptive Resample-Move Algorithm for Estimating Normalizing Constants" (2016) 

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Generative Temporal Models with Spatial Memory for Partially Observed Environments


Jul 19, 2018
Marco Fraccaro, Danilo Jimenez Rezende, Yori Zwols, Alexander Pritzel, S. M. Ali Eslami, Fabio Viola

* ICML 2018 

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A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning


Oct 30, 2017
Marco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther

* NIPS 2017 

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Semi-Supervised Generation with Cluster-aware Generative Models


Apr 03, 2017
Lars Maaløe, Marco Fraccaro, Ole Winther


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Sequential Neural Models with Stochastic Layers


Nov 13, 2016
Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, Ole Winther

* NIPS 2016 

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An Adaptive Resample-Move Algorithm for Estimating Normalizing Constants


Aug 15, 2016
Marco Fraccaro, Ulrich Paquet, Ole Winther

* 11 pages, 5 figures 

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