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A Unified View of Stochastic Hamiltonian Sampling


Jun 30, 2021
Giulio Franzese, Dimitrios Milios, Maurizio Filippone, Pietro Michiardi


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Model Selection for Bayesian Autoencoders


Jun 11, 2021
Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Pietro Michiardi, Edwin V. Bonilla, Maurizio Filippone


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All You Need is a Good Functional Prior for Bayesian Deep Learning


Nov 25, 2020
Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Maurizio Filippone


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Sparse within Sparse Gaussian Processes using Neighbor Information


Nov 12, 2020
Gia-Lac Tran, Dimitrios Milios, Pietro Michiardi, Maurizio Filippone

* 10 pages 

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Learning Optimal Conditional Priors For Disentangled Representations


Oct 19, 2020
Graziano Mita, Maurizio Filippone, Pietro Michiardi


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Isotropic SGD: a Practical Approach to Bayesian Posterior Sampling


Jun 09, 2020
Giulio Franzese, Rosa Candela, Dimitrios Milios, Maurizio Filippone, Pietro Michiardi


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A Variational View on Bootstrap Ensembles as Bayesian Inference


Jun 08, 2020
Dimitrios Milios, Pietro Michiardi, Maurizio Filippone


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Rethinking Sparse Gaussian Processes: Bayesian Approaches to Inducing-Variable Approximations


Mar 09, 2020
Simone Rossi, Markus Heinonen, Edwin V. Bonilla, Zheyang Shen, Maurizio Filippone


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Kernel computations from large-scale random features obtained by Optical Processing Units


Dec 02, 2019
Ruben Ohana, Jonas Wacker, Jonathan Dong, Sébastien Marmin, Florent Krzakala, Maurizio Filippone, Laurent Daudet

* 5 pages, 3 figures, submitted to ICASSP 2020 

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Efficient Approximate Inference with Walsh-Hadamard Variational Inference


Nov 29, 2019
Simone Rossi, Sebastien Marmin, Maurizio Filippone

* Paper accepted at the 4th Workshop on Bayesian Deep Learning (NeurIPS 2019), Vancouver, Canada. arXiv admin note: substantial text overlap with arXiv:1905.11248 

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LIBRE: Learning Interpretable Boolean Rule Ensembles


Nov 15, 2019
Graziano Mita, Paolo Papotti, Maurizio Filippone, Pietro Michiardi


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Sparsification as a Remedy for Staleness in Distributed Asynchronous SGD


Oct 21, 2019
Rosa Candela, Giulio Franzese, Maurizio Filippone, Pietro Michiardi


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Deep Compositional Spatial Models


Jun 06, 2019
Andrew Zammit-Mangion, Tin Lok James Ng, Quan Vu, Maurizio Filippone

* 57 pages, 11 figures 

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Walsh-Hadamard Variational Inference for Bayesian Deep Learning


May 27, 2019
Simone Rossi, Sebastien Marmin, Maurizio Filippone


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A comparative evaluation of novelty detection algorithms for discrete sequences


Feb 28, 2019
Rémi Domingues, Pietro Michiardi, Jérémie Barlet, Maurizio Filippone

* Submitted to Artificial Intelligence Review journal; 24 pages, 4 tables, 11 figures 

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Variational Calibration of Computer Models


Oct 29, 2018
Sébastien Marmin, Maurizio Filippone


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Good Initializations of Variational Bayes for Deep Models


Oct 18, 2018
Simone Rossi, Pietro Michiardi, Maurizio Filippone

* 8 pages of main paper (+2 for references and +5 of supplement material) 

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Constraining the Dynamics of Deep Probabilistic Models


Jun 18, 2018
Marco Lorenzi, Maurizio Filippone

* 13 pages 

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Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification


May 28, 2018
Dimitrios Milios, Raffaello Camoriano, Pietro Michiardi, Lorenzo Rosasco, Maurizio Filippone


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Calibrating Deep Convolutional Gaussian Processes


May 26, 2018
Gia-Lac Tran, Edwin V. Bonilla, John P. Cunningham, Pietro Michiardi, Maurizio Filippone

* 12 pages 

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Pseudo-extended Markov chain Monte Carlo


Aug 17, 2017
Christopher Nemeth, Fredrik Lindsten, Maurizio Filippone, James Hensman


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Entropic Trace Estimates for Log Determinants


Apr 24, 2017
Jack Fitzsimons, Diego Granziol, Kurt Cutajar, Michael Osborne, Maurizio Filippone, Stephen Roberts

* 16 pages, 4 figures, 2 tables, 2 algorithms 

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Bayesian Inference of Log Determinants


Apr 05, 2017
Jack Fitzsimons, Kurt Cutajar, Michael Osborne, Stephen Roberts, Maurizio Filippone

* 12 pages, 3 figures 

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AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models


Mar 06, 2017
Karl Krauth, Edwin V. Bonilla, Kurt Cutajar, Maurizio Filippone

* Edited results on RECTANGLES-IMAGE and related comments; minor additional edits 

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Random Feature Expansions for Deep Gaussian Processes


Mar 01, 2017
Kurt Cutajar, Edwin V. Bonilla, Pietro Michiardi, Maurizio Filippone


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Mini-Batch Spectral Clustering


Aug 12, 2016
Yufei Han, Maurizio Filippone


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Preconditioning Kernel Matrices


May 25, 2016
Kurt Cutajar, Michael A. Osborne, John P. Cunningham, Maurizio Filippone


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Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)


Sep 03, 2015
Maurizio Filippone, Raphael Engler

* 10 pages - paper accepted at ICML 2015 

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MCMC for Variationally Sparse Gaussian Processes


Jun 12, 2015
James Hensman, Alexander G. de G. Matthews, Maurizio Filippone, Zoubin Ghahramani

* 16 pages 

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