paper-conference

On Stein variational neural network ensembles

Francesco D'Angelo, Vincent Fortuin, Florian Wenzel

PACOH: Bayes-optimal meta-learning with PAC-guarantees

Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause

PCA Subspaces Are Not Always Optimal for Bayesian Learning

Alexandre Bense, Amir Joudaki, Tim GJ Rudner, Vincent Fortuin

Reproducibility report for ''Interpretable Complex-Valued Neural Networks for Privacy Protection''

Arsen Sheverdin, Noud Corten, Alko Knijff, Georg Lange

Scalable Gaussian process variational autoencoders

Metod Jazbec, Matt Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch

Scalable marginal likelihood estimation for model selection in deep learning

Alexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rätsch, Mohammad Emtiyaz Khan

T-DPSOM: An interpretable clustering method for unsupervised learning of patient health states

Laura Manduchi, Matthias Hüser, Martin Faltys, Julia Vogt, Gunnar Rätsch, Vincent Fortuin

Conservative uncertainty estimation by fitting prior networks

Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner

GP-VAE: Deep probabilistic time series imputation

Vincent Fortuin, Dmitry Baranchuk, Gunnar Rätsch, Stephan Mandt

Stability analysis of artificial ice islands by methods of mathematical modeling

Igor Borisovich Petrov, Maksim Viktorovich Muratov, Fedor Igorevich Sergeev