| Probabilistic line searches for stochastic optimization M Mahsereci, P Hennig Advances in Neural Information Processing Systems, 181-189, 2015 | 151 | 2015 |
| Probabilistic line searches for stochastic optimization M Mahsereci, P Hennig Advances in Neural Information Processing Systems 28, 2015 | 151 | 2015 |
| Emulation of physical processes with emukit A Paleyes, M Pullin, M Mahsereci, N Lawrence, J González Second Workshop on Machine Learning and the Physical Sciences, NeurIPS, 2019 | 99 | 2019 |
| Early stopping without a validation set M Mahsereci, L Balles, C Lassner, P Hennig arXiv preprint arXiv:1703.09580, 2017 | 98 | 2017 |
| Active Multi-Information Source Bayesian Quadrature A Gessner, J Gonzalez, M Mahsereci Conference on Uncertainty in Artificial Intelligence (UAI), 2019 | 28 | 2019 |
| ProbNum: Probabilistic Numerics in Python J Wenger, N Krämer, M Pförtner, J Schmidt, N Bosch, N Effenberger, ... arXiv preprint arXiv:2112.02100, 2021 | 9 | 2021 |
| Spectral analysis of PG 1034+ 001, the exciting star of Hewett 1 M Mahsereci, E Ringat, T Rauch, K Werner, JW Kruk Planetary Nebulae: An Eye to the Future, Proceedings of the International …, 2012 | 6 | 2012 |
| A Fourier State Space Model for Bayesian ODE Filters H Kersting, M Mahsereci arXiv preprint arXiv:2007.09118, 2020 | 5 | 2020 |
| ProbNum: probabilistic numerics in python,(2021) J Wenger, N Krämer, M Pförtner, J Schmidt, N Bosch, N Effenberger, ... arXiv preprint arXiv:2112.02100, 0 | 5 | |
| Probabilistic Approaches to Stochastic Optimization M Mahsereci Universität Tübingen, 2018 | 4 | 2018 |
| Automating stochastic optimization with gradient variance estimates L Balles, M Mahsereci, P Hennig ICML AutoML Workshop, 13, 2017 | 4 | 2017 |
| Dynamic Pruning of a Neural Network via Gradient Signal-to-Noise Ratio JN Siems, A Klein, C Archambeau, M Mahsereci 8th ICML Workshop on Automated Machine Learning (AutoML), 2021 | 3 | 2021 |
| Emukit: A Python toolkit for decision making under uncertainty A Paleyes, M Mahsereci, ND Lawrence Python in Science Conference, 68-75, 2023 | 2 | 2023 |
| Comparing Scale Parameter Estimators for Gaussian Process Regression: Cross Validation and Maximum Likelihood M Naslidnyk, M Kanagawa, T Karvonen, M Mahsereci arXiv preprint arXiv:2307.07466, 2023 | 1 | 2023 |
| Invariant Priors for Bayesian Quadrature M Naslidnyk, J Gonzalez, M Mahsereci arXiv preprint arXiv:2112.01578, 2021 | 1 | 2021 |
| Probabilistic Numerical Methods-From Theory to Implementation (Dagstuhl Seminar 21432) P Hennig, ICF Ipsen, M Mahsereci, T Sullivan Dagstuhl Reports 11 (9), 2022 | | 2022 |
| On acquisition functions for active multi-source Bayesian quadrature A Gessner, M Mahsereci, J González | | 2018 |
| Spectral Analysis of PG 1034+ 001, the Exciting Star of Hewett 1 JW Kruk, M Mahsereci, E Ringat, T Rauch, K Werner | | 2011 |
