| Avoiding numerical pitfalls in social force models G Köster, F Treml, M Gödel Physical Review E 87 (6), 063305, 2013 | 81 | 2013 |
| Vadere: An open-source simulation framework to promote interdisciplinary understanding B Kleinmeier, B Zönnchen, M Gödel, G Köster arXiv preprint arXiv:1907.09520, 2019 | 61 | 2019 |
| Robust ensemble time onboard a satellite M Gödel, J Furthner Proceedings of the 48th annual precise time and time interval systems and …, 2017 | 28 | 2017 |
| Sensitivity Analysis for Microscopic Crowd Simulation M Gödel, R Fischer, G Köster Algorithms - Special Issue Methods and Applications of Uncertainty …, 2020 | 17 | 2020 |
| Bayesian inference methods to calibrate crowd dynamics models for safety applications M Gödel, N Bode, G Köster, HJ Bungartz Safety science 147, 105586, 2022 | 16 | 2022 |
| Comparison between simulation and hardware realization for different clock steering techniques M Gödel, TD Schmidt, J Furthner Metrologia 56 (3), 035001, 2019 | 13 | 2019 |
| Investigation of pole placement technique for clock steering TD Schmidt, M Gödel, J Furthner Proceedings of the 49th Annual Precise Time and Time Interval Systems and …, 2018 | 10 | 2018 |
| Kalman filter approaches for a mixed clock ensemble M Gödel, TD Schmidt, J Furthner 2017 Joint Conference of the European Frequency and Time Forum and IEEE …, 2017 | 10 | 2017 |
| Modelling airborne transmission of SARS-CoV-2 at a local scale S Rahn, M Gödel, G Köster, G Hofinger Plos one 17 (8), e0273820, 2022 | 6 | 2022 |
| Dynamics of a simulated demonstration march: An efficient sensitivity analysis S Rahn, M Gödel, R Fischer, G Köster Sustainability 13 (6), 3455, 2021 | 5 | 2021 |
| Can we learn where people go? M Gödel, G Köster, D Lehmberg, M Gruber, A Kneidl, F Sesser arXiv preprint arXiv:1812.03719, 2018 | 4 | 2018 |
| Operational composite clock for SBAS systems M Suess, M Goedel, J Furthner, M Meurer Proceedings of the 27th International Technical Meeting of the Satellite …, 2014 | 4 | 2014 |
| Applying Bayesian inversion with Markov Chain Monte Carlo to Pedestrian Dynamics M Gödel, R Fischer, G Köster Proceedings of the UNCECOMP, 2019 | 3 | 2019 |
| Implementation issues of force based pedestrian motion models G Köster, M Gödel Traffic and Granular Flow'13, 63-71, 2015 | 2 | 2015 |
| Toward learning dynamic origin-destination matrices from crowd density heatmaps M Gödel, D Lehmberg, R Brydon, E Bosina, G Köster Journal of Statistical Mechanics: Theory and Experiment 2022 (5), 053401, 2022 | 1 | 2022 |
| Systematic parameter analysis to reduce uncertainty in crowd simulations M Gödel Technische Universität München, 2022 | 1 | 2022 |
| Can we learn where people come from? Retracing of origins in merging situations M Gödel, L Spataro, G Köster arXiv preprint arXiv:2012.11527, 2020 | | 2020 |
| Towards Inferring Input Parameters from Measurements: Bayesian Inversion for a Bottleneck Scenario M Gödel, R Fischer, G Köster Traffic and Granular Flow 2019, 93-102, 2020 | | 2020 |
Johann FurthnerWissenschaftlicher Mitarbeiter, DLR Institut für Kommunikation und Navigation在 dlr.de 的电子邮件经过验证
