Johannes S. Otterbach

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 14

Top Topics

Top Venues

IFIP Networking

Comput. Commun.

Publications

Olga Kondrateva, Stefan Dietzel, Maximilian Schambach, Johannes S. Otterbach, Björn Scheuermann
Progressive updates of convolutional neural networks for enhanced reliability in small satellite applications. Comput. Commun. 225 (2024)
Alexander Koenig, Maximilian Schambach, Johannes S. Otterbach
Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation. CVPR Workshops (2023)
Julien Siems, Maximilian Schambach, Sebastian Schulze, Johannes S. Otterbach
Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management. CoRR (2023)
Alexander Koenig, Maximilian Schambach, Johannes S. Otterbach
Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation. CoRR (2023)
Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models. CoRR (2023)
Olga Kondrateva, Stefan Dietzel, Maximilian Schambach, Johannes S. Otterbach, Björn Scheuermann
Filling the Gap: Fault-Tolerant Updates of On-Satellite Neural Networks Using Vector Quantization. IFIP Networking (2023)
Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models. NeurIPS (2023)
Maximilian Schambach, Dominique Paul, Johannes S. Otterbach
Scaling Experiments in Self-Supervised Cross-Table Representation Learning. CoRR (2023)
Felix Pieper, Konstantin Ditschuneit, Martin Genzel, Alexandra Lindt, Johannes S. Otterbach
Self-Distilled Representation Learning for Time Series. CoRR (2023)
Konstantin Ditschuneit, Johannes S. Otterbach
Auto-Compressing Subset Pruning for Semantic Image Segmentation. CoRR (2022)
Simon Ohler, Daniel Brady, Winfried Lötzsch, Michael Fleischhauer, Johannes S. Otterbach
Towards Learning Self-Organized Criticality of Rydberg Atoms using Graph Neural Networks. CoRR (2022)
Winfried Lötzsch, Simon Ohler, Johannes S. Otterbach
Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks. CoRR (2022)
Konstantin Ditschuneit, Johannes S. Otterbach
Auto-Compressing Subset Pruning for Semantic Image Segmentation. GCPR (2022)
Johannes S. Otterbach
Optimizing Variational Quantum Circuits using Evolution Strategies. CoRR (2018)