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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

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

Scalable Gaussian Processes on Discrete Domains

Vincent Fortuin, Gideon Dresdner, Heiko Strathmann, Gunnar Rätsch