Malte Probst
Malte Probst
Senior Scientist, Honda Research Institute
Verified email at
Cited by
Cited by
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
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
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
Harmless overfitting: Using denoising autoencoders in estimation of distribution algorithms
M Probst, F Rothlauf
Journal of Machine Learning Research 21 (78), 1-31, 2020
Denoising autoencoders for fast combinatorial black box optimization
M Probst
Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015
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
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
Deep Boltzmann machines in estimation of distribution algorithms for combinatorial optimization
M Probst, F Rothlauf
arXiv preprint arXiv:1509.06535, 2015
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
Generative adversarial networks in estimation of distribution algorithms for combinatorial optimization
M Probst
arXiv preprint arXiv:1509.09235, 2015
EDL-Editor: Eine Anwendung zur automatischen Aufbereitung von Vorlesungsvideos
S Kopf, F Lampi, T King, M Probst, W Effelsberg
Gesellschaft für Informatik eV, 2007
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
The set autoencoder: Unsupervised representation learning for sets
M Probst
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
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
Generative Adversarial Networks in Estimation of Distribution Algorithms for Combinatorial Optimization. CoRR abs/1509.09235 (2015)
M Probst
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
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
Method for assisting a driver, driver assistance system, and vehicle including such driver assistance system
J Eggert, T Puphal, M Probst
US Patent 11,220,261, 2022
Considering Human Factors in Risk Maps for Robust and Foresighted Driver Warning
T Puphal, R Hirano, M Probst, R Wenzel, A Kimata
2023 32nd IEEE International Conference on Robot and Human Interactive …, 2023
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