Publications

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2025

Choose Your Model Size: Any Compression of Large Language Models Without Re-Computation.

Martin Genzel, Patrick Putzky, Pengfei Zhao, Sebastian Schulze, Mattes Mollenhauer, Robert Seidel, Stefan Dietzel, Thomas Wollmann.

Transactions on Machine Learning Research.

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Regularized least squares learning with heavy-tailed noise is minimax optimal.

Mattes Mollenhauer, Nicole Mücke, Dimitri Meunier, Arthur Gretton.

Advances in Neural Information Processing Systems (NeurIPS).

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Can automatic rodent behavior analysis using AI/ML contribute to drug safety? Initial insights from DeepRod.

B. Weiss, K. Eschmann, C. Weinandi, P. Schwarz, F.-Z. Khamlichi, H. Behnke, M. Garafolj, O. Akhtar, A. Loy, H. Schauerte, T. Wollmann, G. Rast.

Toxicology Letters.

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Robust Weight Imprinting: Insights from Neural Collapse and Proxy-Based Aggregation.

Justus Westerhoff, Golzar Atefi, Mario Koddenbrock, Alexei Figueroa, Alexander Löser, Erik Rodner, Felix A. Gers.

Transactions on Machine Learning Research.

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Compressing large language models to any size without re-computation.

Martin Genzel, Patrick Putzky, Pengfei Zhao, Sebastian Schulze, Mattes Mollenhauer, Robert Seidel, Stefan Dietzel, Thomas Wollmann.

ICML Workshop ES-FoMo.

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Deep Joint Source-Channel Coding for Small Satellite Applications.

Olga Kondrateva, Grace Li Zhang, Julian Zobel, Björn Scheuermann, Stefan Dietzel.

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2024

Squirrel: A Python library that enables ML teams to share, load, and transform data in a collaborative, flexible, and efficient way.

Alireza Sohofi, Tiansu Yu, Alp Aribal, Winfried Loetzsch, Thomas Wollmann.

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Memorization with neural networks: going beyond the worst case scenario.

Sjoerd Dirksen, Patrick Finke, Martin Genzel.

Journal of Machine Learning Research.

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Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms.

Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li.

Advances in Neural Information Processing Systems (NeurIPS).

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Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm.

Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton.

Journal of Machine Learning Research.

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Adaptable Deep Joint Source-and-Channel Coding for Small Satellite Applications.

Olga Kondrateva, Stefan Dietzel, Björn Scheuermann.

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Quantority: Parameter Prioritization for Incremental Updates of Convolutional Neural Networks in Small Satellite Missions.

Olga Kondrateva, Stefan Dietzel, Björn Scheuermann.

IFIP Networking Conference.

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DeepRod: A human-in-the-loop system for automatic rodent behavior analysis.

Adrian Loy, Miha Garafolj, Heike Schauerte, Hanna Behnke, Cyrille Charnier, Philipp Schwarz, Georg Rast, Thomas Wollmann.

ICML Workshop DMLR.

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Progressive Updates of Convolutional Neural Networks for Enhanced Reliability in Small Satellite Applications.

Olga Kondrateva, Stefan Dietzel, Maximilian Schambach, Johannes Otterbach, Björn Scheuermann.

Computer Communications.

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Explainability and Interpretability in Electric Load Forecasting Using Machine Learning Techniques.

Lukas Baur, Konstantin Ditschuneit, Maximilian Schambach, Can Kaymakci, Thomas Wollmann, Alexander Sauer.

Energy and AI.

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Integrating Cloud Computing, Bayesian Optimization, and Neural-Additive Modeling for Enhanced CAM Systems in 5-Axis Milling.

Viktor Rudel, Georg Vinogradov, Philipp Ganser, Thomas Bergs, Christopher Vahl, Markus Frings, Valentina König, Maximilian Schambach, Stefan Dietzel, Michael Königs.

Procedia CIRP.

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2023

Multiscale Neural Operators for Solving Time-Independent PDEs.

Winfried Ripken, Lisa Coiffard, Felix Pieper, Sebastian Dziadzio.

NeurIPS Workshop DLDE.

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Scaling Experiments in Self-Supervised Cross-Table Representation Learning.

Maximilian Schambach, Dominique Paul, Johannes S. Otterbach.

NeurIPS Workshop TRL.

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Towards Tabular Foundation Models - Status Quo, Challenges, and Opportunities.

Maximilian Schambach.

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Self-distilled Representation Learning for Time Series.

Felix Pieper, Konstantin Ditschuneit, Martin Genzel, Alexandra Lindt, Johannes Otterbach.

NeurIPS Workshop SSL.

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Curve Your Enthusiasm: Concurvity Regularization in Differentiable GAMs.

Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes Otterbach, Martin Genzel.

Advances in Neural Information Processing Systems (NeurIPS).

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Joint source and channel coding for small satellite applications.

Olga Kondrateva, Stefan Dietzel, Björn Scheuermann.

IEEE Conference on Local Computer Networks (LCN).

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Filling the Gap: Fault-Tolerant Updates of On-Satellite Neural Networks Using Vector Quantization.

Olga Kondrateva, Stefan Dietzel, Maximilian Schambach, Johannes Otterbach, Björn Scheuermann.

IFIP Networking Conference.

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Parameter Prioritization for Efficient Transmission of Neural Networks in Small Satellite Applications.

Olga Kondrateva, Stefan Dietzel, Ansgar Lößer, Björn Scheuermann.

Mediterranean Communication and Computer Networking Conference (MedComNet).

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Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation.

Alexander Koenig, Maximilian Schambach, Johannes S. Otterbach.

CVPR Workshop SAIAD.

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SECREDAS: Safe and (Cyber-) Secure Cooperative and Automated Mobility.

Chris van der Ploeg, Jacco van de Sluis, Sebastian Gerres, Szabolcs Novaczki, András Wippelhauser, Eric Nassor, Julien Sevin, András Gazdag, Gergely Biczók.

IFAC World Congress.

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NAM-CAM: Neural-Additive Models for Semi-analytic Descriptions of CAM Simulations.

Konstantin Ditschuneit, Adem Frenk, Markus Frings, Viktor Rudel, Stefan Dietzel, Johannes S. Otterbach.

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Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management.

Julien Siems, Maximilian Schambach, Sebastian Schulze, Johannes S. Otterbach.

ICLR Workshop AI4ABM.

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2022

Auto-Compressing Subset Pruning for Semantic Image Segmentation.

Konstantin Ditschuneit, Johannes S. Otterbach.

Pattern recognition.

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Towards Learning Self-Organized Criticality of Rydberg Atoms using Graph Neural Networks.

Simon Ohler, Daniel Steven Brady, Winfried Lötzsch, Michael Fleischhauer, Johannes Otterbach.

ICML Workshop AI4Science.

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Scalable Flow Optimization for Small Satellite Networks using Benders Decomposition.

Olga Kondrateva, Stefan Dietzel, Björn Scheuermann.

IEEE International Symposium on a World of Wireless, Mobile, and Multimedia Networks (WoWMoM).

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Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks.

Winfried Lötzsch, Simon Ohler, Johannes S. Otterbach.

ICML Workshop AI4Science.

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2021

Chameleon: A semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs.

Johannes Otterbach, Thomas Wollmann.

GI Computer Science.

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DAAIN: Detection of Anomalous and Adversarial Input using Normalizing Flows.

Samuel von Baußnern, Johannes Otterbach, Adrian Loy, Mathieu Salzmann, Thomas Wollmann.

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MEAL: Manifold Embedding-based Active Learning.

Deepthi Sreenivasaiah, Johannes Otterbach, Thomas Wollmann.

ICCV Workshops.

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