| Understanding probabilistic sparse Gaussian process approximations M Bauer, M van der Wilk, CE Rasmussen Advances in neural information processing systems, 1533-1541, 2016 | 193 | 2016 |
| Meta-learning probabilistic inference for prediction J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner arXiv preprint arXiv:1805.09921, 2018 | 128 | 2018 |
| Resampled priors for variational autoencoders M Bauer, A Mnih The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 64 | 2019 |
| Discriminative k-shot learning using probabilistic models M Bauer, M Rojas-Carulla, JB Swiatkowski, B Schölkopf, RE Turner 2nd Bayesian Deep Learning Workshop, NIPS 2017, 2017 | 55* | 2017 |
| Learning Invariances using the Marginal Likelihood M van der Wilk, M Bauer, ST John, J Hensman Advances in Neural Information Processing Systems, 9938-9948, 2018 | 27 | 2018 |
| Ecological feedback in quorum-sensing microbial populations can induce heterogeneous production of autoinducers M Bauer, J Knebel, M Lechner, P Pickl, E Frey Elife 6, e25773, 2017 | 24 | 2017 |
| Scalable marginal likelihood estimation for model selection in deep learning A Immer, M Bauer, V Fortuin, G Rätsch, ME Khan arXiv preprint arXiv:2104.04975, 2021 | 12 | 2021 |
| Improving predictions of Bayesian neural nets via local linearization A Immer, M Korzepa, M Bauer International Conference on Artificial Intelligence and Statistics, 703-711, 2021 | 12* | 2021 |
| Interpretable and differentially private predictions F Harder, M Bauer, M Park Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4083-4090, 2020 | 12 | 2020 |
| Automatic estimation of modulation transfer functions M Bauer, V Volchkov, M Hirsch, B Schcölkopf 2018 IEEE International Conference on Computational Photography (ICCP), 1-12, 2018 | 4 | 2018 |
| VERSA: Versatile and efficient few-shot learning J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner Advances in Neural Information Processing Systems, 1-9, 2018 | 4 | 2018 |
| Lindblad driving for nonequilibrium steady-state transport for noninteracting quantum impurity models M Bauer Bachelor Thesis (University of Munich, 2011), 2001 | 3 | 2001 |
| Consolidating the Meta-Learning Zoo: A Unifying Perspective as Posterior Predictive Inference J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner Meta Learning Workshop, NeurIPS 2018, 2018 | 2 | 2018 |
| Laplace Redux--Effortless Bayesian Deep Learning E Daxberger, A Kristiadi, A Immer, R Eschenhagen, M Bauer, P Hennig arXiv preprint arXiv:2106.14806, 2021 | 1 | 2021 |
| Generalized Doubly Reparameterized Gradient Estimators M Bauer, A Mnih arXiv preprint arXiv:2101.11046, 2021 | 1 | 2021 |
| Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning M Bauer University of Cambridge, 2020 | | 2020 |
| Deliverable D7. 1 Project website L Nixon, M Bauer | | 2011 |
Richard E TurnerProfessor, University of CambridgeVerified email at cam.ac.uk
