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Bayesian Neural Network Priors Revisited

Deep Neural Networks as Point Estimates for Deep Gaussian Processes

GPflux: A Library for Deep Gaussian Processes

The Promises and Pitfalls of Deep Kernel Learning

A Framework for Interdomain and Multioutput Gaussian Processes

Capsule Networks -- A Probabilistic Perspective

Design of Experiments for Verifying Biomolecular Networks

On the Benefits of Invariance in Neural Networks

Revisiting the Train Loss: an Efficient Performance Estimator for Neural Architecture Search

Variational Orthogonal Features