| Flexible statistical inference for mechanistic models of neural dynamics JM Lueckmann, PJ Goncalves, G Bassetto, K Öcal, M Nonnenmacher, ... Advances in neural information processing systems 30, 2017 | 276 | 2017 |
| 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 | 225 | 2020 |
| Parameter estimation for biochemical reaction networks using Wasserstein distances K Öcal, R Grima, G Sanguinetti Journal of Physics A: Mathematical and Theoretical 53 (3), 034002, 2019 | 31 | 2019 |
| Approximating solutions of the chemical master equation using neural networks A Sukys, K Öcal, R Grima Iscience 25 (9), 2022 | 26 | 2022 |
| Inference and uncertainty quantification of stochastic gene expression via synthetic models K Öcal, MU Gutmann, G Sanguinetti, R Grima Journal of The Royal Society Interface 19 (192), 20220153, 2022 | 11 | 2022 |
| A stochastic vs deterministic perspective on the timing of cellular events L Ham, MA Coomer, K Öcal, R Grima, MPH Stumpf Nature Communications 15 (1), 5286, 2024 | 7* | 2024 |
| Model reduction for the chemical master equation: an information-theoretic approach K Öcal, G Sanguinetti, R Grima The Journal of Chemical Physics 158 (11), 2023 | 6 | 2023 |
| Statistical inference for analyzing sloppiness in neuroscience models M Deistler, GJ Pedro, JM Lueckmann, K Oecal, DS Greenberg, JH Macke Bernstein Conference 2019, Berlin, Germany, 2019 | 2 | 2019 |
| Incorporating extrinsic noise into mechanistic modelling of single-cell transcriptomics K Öcal bioRxiv, 2023.09. 30.560282, 2023 | 1 | 2023 |
| Flexible statistical inference for mechanistic models of neural dynamics P Goncalves, JM Lueckmann, G Bassetto, K Oecal, M Nonnenmacher, ... Bonn Brain 3 Conference 2018, Bonn, Germany, 2018 | 1 | 2018 |
| A universal formula explains cell size distributions in lineages K Öcal, MPH Stumpf arXiv preprint arXiv:2411.08327, 2024 | | 2024 |
| Adaptively learned calibration kernels for stable importance sampling in regression ABC M Nonnenmacher, K Oecal, JH Macke ISBA 2018 Workshop'ABC in Edinburgh', 2018, Edinburgh, UK, 2018 | | 2018 |
Jakob MackeMachine Learning in Science, Tübingen UniversityVerified email at uni-tuebingen.de
