| SBI--A toolkit for simulation-based inference A Tejero-Cantero, J Boelts, M Deistler, JM Lueckmann, C Durkan, ... arXiv preprint arXiv:2007.09114, 2020 | 213 | 2020 |
| Benchmarking simulation-based inference JM Lueckmann, J Boelts, D Greenberg, P Goncalves, J Macke International conference on artificial intelligence and statistics, 343-351, 2021 | 154 | 2021 |
| Flexible and efficient simulation-based inference for models of decision-making J Boelts, JM Lueckmann, R Gao, JH Macke Elife 11, e77220, 2022 | 32 | 2022 |
| GATSBI: Generative adversarial training for simulation-based inference P Ramesh, JM Lueckmann, J Boelts, Á Tejero-Cantero, DS Greenberg, ... arXiv preprint arXiv:2203.06481, 2022 | 26 | 2022 |
| Decoding of imaginary motor movements of fists applying spatial filtering in a BCI simulated application J Boelts, A Cerquera, AF Ruiz-Olaya Artificial Computation in Biology and Medicine: International Work …, 2015 | 8 | 2015 |
| Comparing neural simulations by neural density estimation J Boelts, JM Lueckmann, PJ Goncalves, H Sprekeler, JH Macke 2019 Conference on Cognitive Computational Neuroscience, 13-16 September …, 2019 | 5 | 2019 |
| Proceedings of The 24th International Conference on Artificial Intelligence and Statistics JM Lueckmann, J Boelts, DS Greenberg, PJ Gonçalves, JH Macke, ... PMLR, 2021 | 3 | 2021 |
| Simulation-based inference for efficient identification of generative models in computational connectomics J Boelts, P Harth, R Gao, D Udvary, F Yáñez, D Baum, HC Hege, ... PLOS Computational Biology 19 (9), e1011406, 2023 | 2 | 2023 |
| Model selection via neural density estimation J Boelts, JM Lueckmann, P Goncalves, H Sprekeler, JH Macke Conference in Cognitive Computing 2018, Hannover, Germany, 2018 | 1 | 2018 |
| Advancing methods and applicability of simulation-based inference in neuroscience J Bölts Universität Tübingen, 2023 | | 2023 |
| Simulation-based inference for efficient identification of generative models in computational connectomics JH Macke, M Oberlaender, HC Hege, D Baum, F Yáñez, R Gao, P Harth, ... bio Rxiv, 2023 | | 2023 |
| sbi: Simulation-based inference toolkit A Tejero-Cantero, J Boelts, M Deistler, JM Lueckmann, C Durkan, ... Astrophysics Source Code Library, ascl: 2306.002, 2023 | | 2023 |
| GATSBI: Generative Adversarial Training for Simulation-Based Inference JH Macke, PJ Gonçalves, DS Greenberg, Á Tejero-Cantero, J Boelts, ... arXiv, 2022 | | 2022 |
| Benchmarking Simulation-Based Inference J Boelts, JM Lückmann, JH Macke, DS Greenberg, PJ Gonçalves International Conference on Artificial Intelligence and Statistics, 2021 | | 2021 |
| Bayesian inference for synaptic connectivity rules in anatomically realistic cortical connectomes J Boelts, P Harth, F Yanez, H Hege, M Oberlaender, JH Macke Bernstein Conference 2019, 2019 | | 2019 |
| Model Comparison in Approximate Bayesian Computation J Boelts Technische Universität Berlin, 2018 | | 2018 |
| Online Decoding of Contour Perception Through EEG J Boelts Institute of Cognitive Science, 2015 | | 2015 |
Jakob MackeMachine Learning in Science, Tübingen University在 uni-tuebingen.de 的电子邮件经过验证
