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Deep Classifiers with Label Noise Modeling and Distance Awareness

Vincent Fortuin, Mark Collier, Florian Wenzel, James Allingham, Jeremiah Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou

Priors in Bayesian Deep Learning: A Review

We provide a comprehensive review of the recent advances regarding the choice of priors for Bayesian neural networks, variational autoencoders, and (deep) Gaussian processes.

Vincent Fortuin

Sparse MoEs meet Efficient Ensembles

James Allingham, Florian Wenzel, Zelda Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton

BNNpriors: A library for Bayesian neural network inference with different prior distributions

Vincent Fortuin, Adrià Garriga-Alonso, Mark van der Wilk, Laurence Aitchison

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

Margherita Rosnati, Vincent Fortuin

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

Andreas Kopf, Vincent Fortuin, Vignesh Ram Somnath, Manfred Claassen

Sparse Gaussian Processes on Discrete Domains

Vincent Fortuin, Gideon Dresdner, Heiko Strathmann, Gunnar Rätsch