Understanding Probabilistic Sparse Gaussian Process Approximations. - Matthias Bauer 001; Mark van der Wilk; Carl Edward Rasmussen (NIPS, 2016)

Discriminative k-shot learning using probabilistic models. - Matthias Bauer 001; Mateo Rojas-Carulla; Jakub Bartlomiej Swiatkowski; Bernhard Schölkopf; Richard E. Turner (CoRR, 2017)

Automatic estimation of modulation transfer functions. - Matthias Bauer 001; Valentin Volchkov; Michael Hirsch 001; Bernhard Schölkopf (ICCP, 2018)

Learning Invariances using the Marginal Likelihood. - Mark van der Wilk; Matthias Bauer 001; S. T. John; James Hensman (NeurIPS, 2018)

Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning. - Jonathan Gordon 003; John Bronskill; Matthias Bauer 001; Sebastian Nowozin; Richard E. Turner (CoRR, 2018)

Meta-Learning Probabilistic Inference for Prediction. - Jonathan Gordon 003; John Bronskill; Matthias Bauer 001; Sebastian Nowozin; Richard E. Turner (ICLR (Poster), 2019)

Improving predictions of Bayesian neural networks via local linearization. - Alexander Immer; Maciej Korzepa; Matthias Bauer 001 (CoRR, 2020)

Improving predictions of Bayesian neural nets via local linearization. - Alexander Immer; Maciej Korzepa; Matthias Bauer 001 (AISTATS, 2021)

Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning. - Alexander Immer; Matthias Bauer 001; Vincent Fortuin; Gunnar Rätsch; Mohammad Emtiyaz Khan (ICML, 2021)

Laplace Redux - Effortless Bayesian Deep Learning. - Erik A. Daxberger; Agustinus Kristiadi; Alexander Immer; Runa Eschenhagen; Matthias Bauer 001; Philipp Hennig (NeurIPS, 2021)

Regularising for invariance to data augmentation improves supervised learning. - Aleksander Botev; Matthias Bauer 001; Soham De (CoRR, 2022)

Spatial Functa: Scaling Functa to ImageNet Classification and Generation. - Matthias Bauer 001; Emilien Dupont; Andy Brock; Dan Rosenbaum; Jonathan Schwarz; Hyunjik Kim (CoRR, 2023)

C3: High-Performance and Low-Complexity Neural Compression from a Single Image or Video. - Hyunjik Kim; Matthias Bauer 001; Lucas Theis; Jonathan Richard Schwarz; Emilien Dupont (CVPR, 2024)