Learning, planning, and control in a monolithic neural event inference architecture MV Butz, D Bilkey, D Humaidan, A Knott, S Otte Neural Networks 117, 135-144, 2019 | 58 | 2019 |
Recurrent neural networks for fast and robust vibration-based ground classification on mobile robots S Otte, C Weiss, T Scherer, A Zell 2016 IEEE International Conference on Robotics and Automation (ICRA), 5603-5608, 2016 | 40 | 2016 |
Local feature based online mode detection with recurrent neural networks S Otte, D Krechel, M Liwicki, A Dengel 2012 International Conference on Frontiers in Handwriting Recognition, 533-537, 2012 | 38 | 2012 |
Dynamic cortex memory: Enhancing recurrent neural networks for gradient-based sequence learning S Otte, M Liwicki, A Zell Artificial Neural Networks and Machine Learning–ICANN 2014: 24th …, 2014 | 36 | 2014 |
Optimizing recurrent reservoirs with neuro-evolution S Otte, MV Butz, D Koryakin, F Becker, M Liwicki, A Zell Neurocomputing 192, 128-138, 2016 | 35 | 2016 |
Inferring adaptive goal-directed behavior within recurrent neural networks S Otte, T Schmitt, K Friston, MV Butz Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017 | 30 | 2017 |
Vector-AMCL: Vector based adaptive monte carlo localization for indoor maps R Hanten, S Buck, S Otte, A Zell Intelligent Autonomous Systems 14: Proceedings of the 14th International …, 2017 | 24 | 2017 |
JANNLab Neural Network Framework for Java. S Otte, D Krechel, M Liwicki MLDM Posters, 39-46, 2013 | 23 | 2013 |
OCT A-Scan based lung tumor tissue classification with Bidirectional Long Short Term Memory networks S Otte, C Otte, A Schlaefer, L Wittig, G Hüttmann, D Drömann, A Zell 2013 IEEE International Workshop on Machine Learning for Signal Processing …, 2013 | 21 | 2013 |
A Computational Model for the Dynamical Learning of Event Taxonomies. C Gumbsch, S Otte, MV Butz CogSci, 2017 | 19 | 2017 |
Finite volume neural network: Modeling subsurface contaminant transport T Praditia, M Karlbauer, S Otte, S Oladyshkin, MV Butz, W Nowak arXiv preprint arXiv:2104.06010, 2021 | 17 | 2021 |
Composing partial differential equations with physics-aware neural networks M Karlbauer, T Praditia, S Otte, S Oladyshkin, W Nowak, MV Butz International Conference on Machine Learning, 10773-10801, 2022 | 16 | 2022 |
Investigating long short-term memory networks for various pattern recognition problems S Otte, M Liwicki, D Krechel Machine Learning and Data Mining in Pattern Recognition: 10th International …, 2014 | 16 | 2014 |
Learning what and where: Disentangling location and identity tracking without supervision M Traub, S Otte, T Menge, M Karlbauer, J Thuemmel, MV Butz arXiv preprint arXiv:2205.13349, 2022 | 14 | 2022 |
Revisiting deep convolutional neural networks for RGB-D based object recognition L Madai-Tahy, S Otte, R Hanten, A Zell Artificial Neural Networks and Machine Learning–ICANN 2016: 25th …, 2016 | 14 | 2016 |
Robust Visual Terrain Classification with Recurrent Neural Networks. S Otte, S Laible, R Hanten, M Liwicki, A Zell ESANN, 2015 | 13 | 2015 |
A distributed neural network architecture for robust non-linear spatio-temporal prediction M Karlbauer, S Otte, H Lensch, T Scholten, V Wulfmeyer, MV Butz arXiv preprint arXiv:1912.11141, 2019 | 11 | 2019 |
Inherently constraint-aware control of many-joint robot arms with inverse recurrent models S Otte, A Zwiener, MV Butz Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017 | 10 | 2017 |
Estimation of the surface fluxes for heat and momentum in unstable conditions with machine learning and similarity approaches for the LAFE data set V Wulfmeyer, JMV Pineda, S Otte, M Karlbauer, MV Butz, TR Lee, ... Boundary-Layer Meteorology 186 (2), 337-371, 2023 | 9 | 2023 |
Integrative collision avoidance within rnn-driven many-joint robot arms S Otte, L Hofmaier, MV Butz Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018 | 9 | 2018 |