Matthias Bauer

According to our database, Matthias Bauer authored at least 13 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

C3: High-performance and low-complexity neural compression from a single image or video.

Hyunjik Kim, Matthias Bauer, Lucas Theis, Jonathan Richard Schwarz, Emilien Dupont

CoRR, 2023

Spatial Functa: Scaling Functa to ImageNet Classification and Generation.

Matthias Bauer, Emilien Dupont, Andy Brock, Dan Rosenbaum, Jonathan Schwarz, Hyunjik Kim

CoRR, 2023

2022

Regularising for invariance to data augmentation improves supervised learning.

Aleksander Botev, Matthias Bauer, Soham De

CoRR, 2022

2021

Laplace Redux - Effortless Bayesian Deep Learning.

Erik Daxberger, Agustinus Kristiadi, Alexander Immer, Runa Eschenhagen, Matthias Bauer, Philipp Hennig

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning.

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

Proceedings of the 38th International Conference on Machine Learning, 2021

Improving predictions of Bayesian neural nets via local linearization.

Alexander Immer, Maciej Korzepa, Matthias Bauer

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Improving predictions of Bayesian neural networks via local linearization.

Alexander Immer, Maciej Korzepa, Matthias Bauer

CoRR, 2020

2019

Meta-Learning Probabilistic Inference for Prediction.

Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning.

Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner

CoRR, 2018

Learning Invariances using the Marginal Likelihood.

Mark van der Wilk, Matthias Bauer, S. T. John, James Hensman

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Automatic estimation of modulation transfer functions.

Matthias Bauer, Valentin Volchkov, Michael Hirsch, Bernhard Schölkopf

Proceedings of the 2018 IEEE International Conference on Computational Photography, 2018

2017

Discriminative k-shot learning using probabilistic models.

Matthias Bauer, Mateo Rojas-Carulla, Jakub Bartlomiej Swiatkowski, Bernhard Schölkopf, Richard E. Turner

CoRR, 2017

2016

Understanding Probabilistic Sparse Gaussian Process Approximations.

Matthias Bauer, Mark van der Wilk, Carl Edward Rasmussen

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016