| SBI--A toolkit for simulation-based inference A Tejero-Cantero*, J Boelts*, M Deistler*, JM Lueckmann*, C Durkan*, ... Journal of Open Source Software 5 (52), 2505, 2020 | 303 | 2020 |
| Training deep neural density estimators to identify mechanistic models of neural dynamics PJ Gonçalves*, JM Lueckmann*, M Deistler*, M Nonnenmacher, K Öcal, ... Elife 9, e56261, 2020 | 240 | 2020 |
| Variational methods for simulation-based inference M Glöckler, M Deistler, JH Macke International Conference on Learning Representations (ICLR), 2021 | 54 | 2021 |
| Truncated proposals for scalable and hassle-free simulation-based inference M Deistler, PJ Goncalves, JH Macke Advances in Neural Information Processing Systems (NeurIPS), 2022 | 50 | 2022 |
| Group equivariant neural posterior estimation M Dax, SR Green, J Gair, M Deistler, B Schölkopf, JH Macke International Conference on Learning Representations (ICLR), 2021 | 33 | 2021 |
| Energy efficient network activity from disparate circuit parameters M Deistler, JH Macke*, PJ Gonçalves* Proceedings of the National Academy of Sciences 119 (44), e2207632119, 2022 | 30* | 2022 |
| All-in-one simulation-based inference M Gloeckler, M Deistler, C Weilbach, F Wood, JH Macke International Conference on Machine Learning (ICML), 2024 | 16 | 2024 |
| Adversarial robustness of amortized Bayesian inference M Glöckler, M Deistler, JH Macke International Conference on Machine Learning (ICML), 2023 | 12 | 2023 |
| Combined statistical-mechanistic modeling links ion channel genes to physiology of cortical neuron types Y Bernaerts, M Deistler, PJ Gonçalves, J Beck, M Stimberg, F Scala, ... bioRxiv, 2023.03. 02.530774, 2023 | 11* | 2023 |
| A practical guide to statistical distances for evaluating generative models in science S Bischoff, A Darcher, M Deistler, R Gao, F Gerken, M Gloeckler, L Haxel, ... Transactions of Machine Learning Research (TMLR), 2024 | 8* | 2024 |
| Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation R Gao*, M Deistler*, JH Macke Advances in Neural Information Processing Systems (NeurIPS), 2023 | 4 | 2023 |
| Deep inverse modeling reveals dynamic-dependent invariances in neural circuit mechanisms R Gao, M Deistler, A Schulz, PJ Gonçalves, JH Macke Biorxiv, 2024.08. 21.608969, 2024 | 3 | 2024 |
| Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations J Beck, N Bosch, M Deistler, KL Kadhim, JH Macke, P Hennig, P Berens International Conference on Machine Learning (ICML), 2024 | 3 | 2024 |
| Efficient identification of informative features in simulation-based inference J Beck, M Deistler, Y Bernaerts, J Macke, P Berens Advances in Neural Information Processing Systems (NeurIPS), 2022 | 3 | 2022 |
| Tactile hallucinations on artificial skin induced by homeostasis in a deep boltzmann machine M Deistler*, Y Yener*, F Bergner, P Lanillos, G Cheng 2019 IEEE International Conference on Cyborg and Bionic Systems (CBS), 48-53, 2019 | 3 | 2019 |
| Statistical inference for analyzing sloppiness in neuroscience models M Deistler, PJ Goncalves, JM Lueckmann, K Oecal, DS Greenberg, ... Bernstein Conference 2019, Berlin, Germany, 2019 | 2 | 2019 |
| Local learning rules to attenuate forgetting in neural networks M Deistler*, M Sorbaro*, ME Rule, MH Hennig arXiv preprint arXiv:1807.05097, 2018 | 2 | 2018 |
| Amortized Bayesian Decision Making for simulation-based models M Gorecki, JH Macke, M Deistler Transactions of Machine Learning Research (TMLR), 2023 | 1 | 2023 |
| sbi reloaded: a toolkit for simulation-based inference workflows J Boelts*, M Deistler*, M Gloeckler, Á Tejero-Cantero, JM Lueckmann, ... arXiv preprint arXiv:2411.17337, 2024 | | 2024 |
| From Simulations to Inference: Using Machine Learning to Tune Patient-Specific Finite-Element Models of the Middle Ear Towards Objective Diagnosis H Motallebzadeh, M Deistler, FM Schönleitner, JH Macke, S Puria bioRxiv, 2024 | | 2024 |
Jakob MackeMachine Learning in Science, Tübingen UniversityVerified email at uni-tuebingen.de