| Scalability of using restricted Boltzmann machines for combinatorial optimization M Probst, F Rothlauf, J Grahl European Journal of Operational Research 256 (2), 368-383, 2017 | 25 | 2017 |
| Optimization of velocity ramps with survival analysis for intersection merge-ins T Puphal, M Probst, Y Li, Y Sakamoto, J Eggert 2018 IEEE Intelligent Vehicles Symposium (IV), 1704-1710, 2018 | 19 | 2018 |
| Probabilistic uncertainty-aware risk spot detector for naturalistic driving T Puphal, M Probst, J Eggert IEEE Transactions on Intelligent Vehicles 4 (3), 406-415, 2019 | 12 | 2019 |
| Denoising autoencoders for fast combinatorial black box optimization M Probst Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015 | 12 | 2015 |
| Deep Boltzmann machines in estimation of distribution algorithms for combinatorial optimization M Probst, F Rothlauf arXiv preprint arXiv:1509.06535, 2015 | 10 | 2015 |
| Harmless overfitting: Using denoising autoencoders in estimation of distribution algorithms M Probst, F Rothlauf The Journal of Machine Learning Research 21 (1), 2992-3022, 2020 | 9 | 2020 |
| Comfortable priority handling with predictive velocity optimization for intersection crossings T Puphal, M Probst, M Komuro, Y Li, J Eggert 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2435-2442, 2019 | 7 | 2019 |
| An implicitly parallel EDA based on restricted boltzmann machines M Probst, F Rothlauf, J Grahl Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014 | 7 | 2014 |
| EDL-Editor: Eine Anwendung zur automatischen Aufbereitung von Vorlesungsvideos S Kopf, F Lampi, T King, M Probst, W Effelsberg DeLFI 2007: 5. e-Learning FachtagungInformatik der Gesellschaft für …, 2007 | 5 | 2007 |
| The set autoencoder: Unsupervised representation learning for sets M Probst | 4 | 2018 |
| Generative adversarial networks in estimation of distribution algorithms for combinatorial optimization M Probst arXiv preprint arXiv:1509.09235, 2015 | 4 | 2015 |
| Asymmetry-based behavior planning for cooperation at shared traffic spaces R Wenzel, M Probst, T Puphal, TH Weisswange, J Eggert 2021 IEEE Intelligent Vehicles Symposium (IV), 1008-1015, 2021 | 2 | 2021 |
| Online and Predictive Warning System for Forced Lane Changes using Risk Maps T Puphal, B Flade, M Probst, V Willert, J Adamy, J Eggert IEEE Transactions on Intelligent Vehicles 7 (3), 616-626, 2021 | 2 | 2021 |
| Generative Adversarial Networks in Estimation of Distribution Algorithms for Combinatorial Optimization. CoRR abs/1509.09235 (2015) M Probst | 2 | 2015 |
| Inferring decision strategies from clickstreams in decision support systems: a new process-tracing approach using state machines J Pfeiffer, M Probst, W Steitz, F Rothlauf Theory-Guided Modeling and Empiricism in Information Systems Research, 145-173, 2011 | 2 | 2011 |
| Automated driving in complex real-world scenarios using a scalable risk-based behavior generation framework M Probst, R Wenzel, T Puphal, M Komuro, TH Weisswange, N Steinhardt, ... 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021 | 1 | 2021 |
| Relate to Predict: Towards Task-Independent Knowledge Representations for Reinforcement Learning T Schnürer, M Probst, HM Gross arXiv preprint arXiv:2212.05298, 2022 | | 2022 |
| Importance Filtering with Risk Models for Complex Driving Situations T Puphal, R Wenzel, B Flade, M Probst, J Eggert 2022 7th International Conference on Robotics and Automation Engineering …, 2022 | | 2022 |
| Method, system and vehicle with an uncertainty-based lane positioning control M Probst, T WEIßWANGE, T Puphal, R Wenzel US Patent App. 17/218,122, 2022 | | 2022 |
| Method, system and vehicle for assisting an operator of the vehicle in assessing a traffic situation with shared traffic space R Wenzel, M Probst, T Puphal, T WEIßWANGE US Patent App. 17/159,126, 2022 | | 2022 |
