paper-conference

Hodge-Aware Contrastive Learning

Alexander Möllers, Alexander Immer, Vincent Fortuin, Elvin Isufi

How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization?

Agustinus Kristiadi, Felix Strieth-Kalthoff, Sriram Ganapathi Subramanian, Vincent Fortuin, Pascal Poupart, Geoff Pleiss

Improving Neural Additive Models with Bayesian Principles

Kouroche Bouchiat, Alexander Immer, Hugo Yèche, Gunnar Rätsch, Vincent Fortuin

Rethinking Exploration in Asynchronous Bayesian Optimization: Standard Acquisition is All You Need

Ben Riegler, James AC Odgers, Vincent Fortuin

Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihood

Rayen Dhahri, Alexander Immer, Betrand Charpentier, Stephan Günnemann, Vincent Fortuin

Stein Variational Newton Neural Network Ensembles

Klemens Flöge, Muhammad Abdul Moeed, Vincent Fortuin

Structured Partial Stochasticity in Bayesian Neural Networks

Tommy Rochussen

Towards Dynamic Feature Acquisition on Medical Time Series by Maximizing Conditional Mutual Information

Fedor Sergeev, Paola Malsot, Gunnar Rätsch, Vincent Fortuin

Understanding pathologies of deep heteroskedastic regression

Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt