Dr.-Ing. Christopher Mutschler

Machine Learning and Data Analytics Lab Department Artificial Intelligence in Biomedical Engineering (AIBE) Lehrstuhl für Informatik 2 (Programmiersysteme)

Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning (2026) Raichur NL, Heublein L, Feigl T, Ruegamer A, Mutschler C, Ott F Unpublished / Preprint C-MCTS: Safe Planning with Monte Carlo Tree Search (2026) Parthasarathy D, Kontes G, Plinge A, Mutschler C Unpublished / Preprint Simplicity is Key: An Unsupervised Pretraining Approach for Sparse Radio Channels (2026) Ott J, Stahlke M, Feigl T, Eskofier B, Mutschler C Unpublished / Preprint Unsupervised Learning of Variational Autoencoders on Cortex-M Microcontrollers (2025) Deutel M, Plinge A, Seuss D, Mutschler C, Hannig F, Teich J Conference contribution, Conference Contribution Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML (2025) Deutel M, Kontes G, Mutschler C, Teich J Journal article, Original article Don’t get me wrong: How to apply deep visual interpretations to time series (2025) Löffler C, Lai WC, Zanca D, Schmidt L, Eskofier B, Mutschler C Journal article Multi-Objective Bayesian Optimization with Reinforcement Learning for Edge Deployment of DNNs on Microcontrollers (2025) Deutel M, Kontes G, Mutschler C, Teich J Conference contribution, Conference Contribution Metric-Based Few-Shot Learning With Triplet Selection for Adaptive GNSS Interference Classification (2025) Ott F, Heublein L, Feigl T, Rügamer A, Mutschler C Journal article Attention-Based Fusion of IQ and FFT Spectrograms with AoA Features for GNSS Jammer Localization (2025) Heublein L, Wielenberg C, Nowak T, Feigl T, Mutschler C, Ott F Conference contribution Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification (2025) Gaikwad NS, Heublein L, Raichur NL, Feigl T, Mutschler C, Ott F Conference contribution