Johannes S. Otterbach

18 papers A* 1B 1Journal 12Unranked 4

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Progressive updates of convolutional neural networks for enhanced reliability in small satellite applications. Comput. Commun. Olga Kondrateva, Stefan Dietzel, Maximilian Schambach, Johannes S. Otterbach, Björn Scheuermann
2023	A*	`conf`	Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models. NeurIPS Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel
2023	J	`jnl`	Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models. CoRR Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel
2023	B	`conf`	Filling the Gap: Fault-Tolerant Updates of On-Satellite Neural Networks Using Vector Quantization. IFIP Networking Olga Kondrateva, Stefan Dietzel, Maximilian Schambach, Johannes S. Otterbach, Björn Scheuermann
2023	J	`jnl`	Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management. CoRR Julien Siems, Maximilian Schambach, Sebastian Schulze, Johannes S. Otterbach
2023	J	`jnl`	Scaling Experiments in Self-Supervised Cross-Table Representation Learning. CoRR Maximilian Schambach, Dominique Paul, Johannes S. Otterbach
2023	J	`jnl`	Self-Distilled Representation Learning for Time Series. CoRR Felix Pieper, Konstantin Ditschuneit, Martin Genzel, Alexandra Lindt, Johannes S. Otterbach
2023	—	`conf`	Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation. CVPR Workshops Alexander Koenig, Maximilian Schambach, Johannes S. Otterbach
2023	J	`jnl`	Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation. CoRR Alexander Koenig, Maximilian Schambach, Johannes S. Otterbach
2022	—	`conf`	Auto-Compressing Subset Pruning for Semantic Image Segmentation. GCPR Konstantin Ditschuneit, Johannes S. Otterbach
2022	J	`jnl`	Auto-Compressing Subset Pruning for Semantic Image Segmentation. CoRR Konstantin Ditschuneit, Johannes S. Otterbach
2022	J	`jnl`	Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks. CoRR Winfried Lötzsch, Simon Ohler, Johannes S. Otterbach
2022	J	`jnl`	Towards Learning Self-Organized Criticality of Rydberg Atoms using Graph Neural Networks. CoRR Simon Ohler, Daniel Brady, Winfried Lötzsch, Michael Fleischhauer, Johannes S. Otterbach
2021	—	`conf`	Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs. GI-Jahrestagung Johannes S. Otterbach, Thomas Wollmann
2021	J	`jnl`	Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs. CoRR Johannes S. Otterbach, Thomas Wollmann
2021	J	`jnl`	DAAIN: Detection of Anomalous and Adversarial Input using Normalizing Flows. CoRR Samuel von Baußnern, Johannes S. Otterbach, Adrian Loy, Mathieu Salzmann, Thomas Wollmann
2021	—	`conf`	MEAL: Manifold Embedding-based Active Learning. ICCVW Deepthi Sreenivasaiah, Johannes S. Otterbach, Thomas Wollmann
2018	J	`jnl`	Optimizing Variational Quantum Circuits using Evolution Strategies. CoRR Johannes S. Otterbach