Malte Probst
Malte Probst
Senior Scientist, Honda Research Institute
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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
Denoising autoencoders for fast combinatorial black box optimization
M Probst
Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015
Deep boltzmann machines in estimation of distribution algorithms for combinatorial optimization
M Probst, F Rothlauf
arXiv preprint arXiv:1509.06535, 2015
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
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
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
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
Generative adversarial networks in estimation of distribution algorithms for combinatorial optimization
M Probst
arXiv preprint arXiv:1509.09235, 2015
Harmless Overfitting: Using Denoising Autoencoders in Estimation of Distribution Algorithms
M Probst, F Rothlauf
Journal of Machine Learning Research 21 (78), 1-31, 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
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
The Set Autoencoder: Unsupervised Representation Learning for Sets
M Probst
Generative Neural Networks for Combinatorial Optimization
M Probst
Johannes Gutenberg-Universität Mainz, 2016
Training a Restricted Boltzmann Machine for classification by labeling model samples
M Probst, F Rothlauf
arXiv preprint arXiv:1509.01053, 2015
Strategies for Improving Camera to Map Alignment
J Silberbauer, B Flade, S Hasler, M Probst, J Eggert
Workshop New Challenges in Neural Computation 2017, 44, 0
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