Maximilian Soelch
Maximilian Soelch
Machine Learning Research Lab, Volkswagen AG
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Zitiert von
Zitiert von
Deep variational bayes filters: Unsupervised learning of state space models from raw data
M Karl, M Soelch, J Bayer, P Van der Smagt
arXiv preprint arXiv:1605.06432, 2016
Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series
M Soelch, J Bayer, M Ludersdorfer, P van der Smagt
arXiv preprint arXiv:1602.07109, 2016
Unsupervised real-time control through variational empowerment
M Karl, P Becker-Ehmck, M Soelch, D Benbouzid, P van der Smagt, ...
The International Symposium of Robotics Research, 158-173, 2019
Latent matters: Learning deep state-space models
A Klushyn, R Kurle, M Soelch, B Cseke, P van der Smagt
Advances in Neural Information Processing Systems 34, 10234-10245, 2021
Approximate bayesian inference in spatial environments
A Mirchev, B Kayalibay, M Soelch, P van der Smagt, J Bayer
arXiv preprint arXiv:1805.07206, 2018
On deep set learning and the choice of aggregations
M Soelch, A Akhundov, P van der Smagt, J Bayer
Artificial Neural Networks and Machine Learning–ICANN 2019: Theoretical …, 2019
Mind the gap when conditioning amortised inference in sequential latent-variable models
J Bayer, M Soelch, A Mirchev, B Kayalibay, P van der Smagt
arXiv preprint arXiv:2101.07046, 2021
Variational tracking and prediction with generative disentangled state-space models
A Akhundov, M Soelch, J Bayer, P van der Smagt
arXiv preprint arXiv:1910.06205, 2019
Detecting anomalies in robot time series data using stochastic recurrent networks
M Sölch
Navigation and planning in latent maps
B Kayalibay, A Mirchev, M Soelch, P Van Der Smagt, J Bayer
FAIM workshop “Prediction and Generative Modeling in Reinforcement Learning 4, 2018
Integrating competency-based education in interactive learning systems
M Sölch, M Aberle, S Krusche
arXiv preprint arXiv:2309.12343, 2023
Is Online Teaching Dead After COVID-19? Student Preferences for Programming Courses
S Manger, M Sölch, M Linhuber, C Weinhuber, P Zagar, S Krusche
2023 IEEE 35th International Conference on Software Engineering Education …, 2023
Uncovering dynamics
MJG Sölch
Technische Universität München, 2021
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