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Bayesian Neural Network Priors Revisited

Feb 12, 2021
Vincent Fortuin, Adrià Garriga-Alonso, Florian Wenzel, Gunnar Rätsch, Richard Turner, Mark van der Wilk, Laurence Aitchison


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On Disentanglement in Gaussian Process Variational Autoencoders

Feb 10, 2021
Simon Bing, Vincent Fortuin, Gunnar Rätsch


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Annealed Stein Variational Gradient Descent

Feb 08, 2021
Francesco D'Angelo, Vincent Fortuin


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Exact Langevin Dynamics with Stochastic Gradients

Feb 02, 2021
Adrià Garriga-Alonso, Vincent Fortuin

* 13 pages, 2 figures. Accepted to the 3rd Symposium on Advances in Approximate Bayesian Inference (AABI 2021) 

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Factorized Gaussian Process Variational Autoencoders

Nov 14, 2020
Metod Jazbec, Michael Pearce, Vincent Fortuin


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Scalable Gaussian Process Variational Autoencoders

Nov 12, 2020
Metod Jazbec, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch


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Sparse Gaussian Process Variational Autoencoders

Oct 23, 2020
Matthew Ashman, Jonathan So, Will Tebbutt, Vincent Fortuin, Michael Pearce, Richard E. Turner

* 19 pages, 6 figures 

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PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees

Feb 13, 2020
Jonas Rothfuss, Vincent Fortuin, Andreas Krause


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Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations

Oct 17, 2019
Andreas Kopf, Vincent Fortuin, Vignesh Ram Somnath, Manfred Claassen

* Submitted as conference paper at Eighth International Conference on Learning Representations (ICLR 2020) 

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Variational PSOM: Deep Probabilistic Clustering with Self-Organizing Maps

Oct 03, 2019
Laura Manduchi, Matthias Hüser, Gunnar Rätsch, Vincent Fortuin


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Deep Multiple Instance Learning for Taxonomic Classification of Metagenomic read sets

Sep 28, 2019
Andreas Georgiou, Vincent Fortuin, Harun Mustafa, Gunnar Rätsch


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MGP-AttTCN: An Interpretable Machine Learning Model for the Prediction of Sepsis

Sep 27, 2019
Margherita Rosnati, Vincent Fortuin


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Multivariate Time Series Imputation with Variational Autoencoders

Jul 12, 2019
Vincent Fortuin, Gunnar Rätsch, Stephan Mandt


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Deep Mean Functions for Meta-Learning in Gaussian Processes

Jan 23, 2019
Vincent Fortuin, Gunnar Rätsch


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Scalable Gaussian Processes on Discrete Domains

Oct 24, 2018
Vincent Fortuin, Gideon Dresdner, Heiko Strathmann, Gunnar Rätsch


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Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series

Oct 05, 2018
Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch


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