Sebastian Otte
Sebastian Otte
Institute for Robotics and Cognitive Systems
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Cited by
Cited by
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
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
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
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
Optimizing recurrent reservoirs with neuro-evolution
S Otte, MV Butz, D Koryakin, F Becker, M Liwicki, A Zell
Neurocomputing 192, 128-138, 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
JANNLab Neural Network Framework for Java.
S Otte, D Krechel, M Liwicki
MLDM Posters, 39-46, 2013
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
A Computational Model for the Dynamical Learning of Event Taxonomies.
C Gumbsch, S Otte, MV Butz
CogSci, 2017
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
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
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
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
Robust Visual Terrain Classification with Recurrent Neural Networks.
S Otte, S Laible, R Hanten, M Liwicki, A Zell
ESANN, 2015
Learning What and Where: Disentangling Location and Identity Tracking Without Supervision
M Traub, S Otte, T Menge, M Karlbauer, J Thuemmel, MV Butz
The Eleventh International Conference on Learning Representations, 2022
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
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
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
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
Inverse Recurrent Models – An Application Scenario for Many-Joint Robot Arm Control
S Otte, A Zwiener, R Hanten, A Zell
International Conference on Artificial Neural Networks, 149-157, 2016
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