Learning event detection rules with noise hidden Markov models. - Christopher Mutschler; Michael Philippsen (AHS, 2012)

Evolutionary algorithms that use runtime migration of detector processes to reduce latency in event-based systems. - Christoffer Löffler; Christopher Mutschler; Michael Philippsen (AHS, 2013)

Reliable speculative processing of out-of-order event streams in generic publish/subscribe middlewares. - Christopher Mutschler; Michael Philippsen (DEBS, 2013)

Demo: do event-based systems have a passion for sports? - Christopher Mutschler; Nicolas Witt; Michael Philippsen (DEBS, 2013)

The DEBS 2013 grand challenge. - Christopher Mutschler; Holger Ziekow; Zbigniew Jerzak (DEBS, 2013)

Distributed Low-Latency Out-of-Order Event Processing for High Data Rate Sensor Streams. - Christopher Mutschler; Michael Philippsen (IPDPS, 2013)

Runtime migration of stateful event detectors with low-latency ordering constraints. - Christopher Mutschler; Michael Philippsen (PerCom Workshops, 2013)

Predictive load management in smart grid environments. - Christopher Mutschler; Christoffer Löffler; Nicolas Witt; Thorsten Edelhäußer; Michael Philippsen (DEBS, 2014)

Adaptive Speculative Processing of Out-of-Order Event Streams. - Christopher Mutschler; Michael Philippsen (ACM Trans. Internet Techn., 2014)

Latency Minimization of Order-Preserving Distributed Event-Based Systems. - Christopher Mutschler (Verlag Dr. Hut, 2014)

Approximative event processing on sensor data streams. - Christoffer Löffler; Christopher Mutschler; Michael Philippsen (DEBS, 2015)

Inter-satellite ranging in the Low Earth Orbit. - Mohammad Alawieh; Niels Hadaschik; Norbert Franke; Christopher Mutschler (CSNDSP, 2016)

Virtual and augmented reality in sports: an overview and acceptance study. - Stefan Gradl; Björn M. Eskofier; Dominic Eskofier; Christopher Mutschler; Stephan Otto (UbiComp Adjunct, 2016)

Low-complexity PDoA-based localization. - Benjamin Sackenreuter; Niels Hadaschik; Marc Fassbinder; Christopher Mutschler (IPIN, 2016)

Social Augmentations in Multi-User Virtual Reality: A Virtual Museum Experience. - Daniel Roth 001; Constantin Kleinbeck; Tobias Feigl; Christopher Mutschler; Marc Erich Latoschik (ISMAR Adjunct, 2017)

Acoustical manipulation for redirected walking. - Tobias Feigl; Eliise Kõre; Christopher Mutschler; Michael Philippsen (VRST, 2017)

Supervised Learning for Yaw Orientation Estimation. - Tobias Feigl; Christopher Mutschler; Michael Philippsen (IPIN, 2018)

Recurrent Neural Networks on Drifting Time-of-Flight Measurements. - Tobias Feigl; Thorsten Nowak; Michael Philippsen; Thorsten Edelhäußer; Christopher Mutschler (IPIN, 2018)

Indoor Positioning Using OFDM-Based Visible Light Communication System. - Birendra Ghimire; Jochen Seitz 002; Christopher Mutschler (IPIN, 2018)

Evaluation Criteria for Inside-Out Indoor Positioning Systems Based on Machine Learning. - Christoffer Löffler; Sascha Riechel; Janina Fischer; Christopher Mutschler (IPIN, 2018)

Convolutional Neural Networks for Position Estimation in TDoA-Based Locating Systems. - Arne Niitsoo; Thorsten Edelhäußer; Christopher Mutschler (IPIN, 2018)

Super-Resolution in RSS-Based Direction-of-Arrival Estimation. - Thorsten Nowak; Markus Hartmann; Jörn Thielecke; Niels Hadaschik; Christopher Mutschler (IPIN, 2018)

Human Compensation Strategies for Orientation Drifts. - Tobias Feigl; Christopher Mutschler; Michael Philippsen (VR, 2018)

Head-to-Body-Pose Classification in No-Pose VR Tracking Systems. - Tobias Feigl; Christopher Mutschler; Michael Philippsen (VR, 2018)

Beyond Replication: Augmenting Social Behaviors in Multi-User Virtual Realities. - Daniel Roth 001; Constantin Kleinbeck; Tobias Feigl; Christopher Mutschler; Marc Erich Latoschik (VR, 2018)

A Location-Based VR Museum. - Jean-Luc Lugrin; Florian Kern; Ruben Schmidt; Constantin Kleinbeck; Daniel Roth 001; Christian Daxer; Tobias Feigl; Christopher Mutschler; Marc Erich Latoschik (VS-GAMES, 2018)

Optical Camera Communication for Active Marker Identification in Camera-based Positioning Systems. - Lorenz Gorse; Christoffer Löffler; Christopher Mutschler; Michael Philippsen (WPNC, 2018)

A Bidirectional LSTM for Estimating Dynamic Human Velocities from a Single IMU. - Tobias Feigl; Sebastian Kram; Philipp Woller; Ramiz H. Siddiqui; Michael Philippsen; Christopher Mutschler (IPIN, 2019)

Deep Reinforcement Learning for Motion Planning of Mobile Robots. - Leonid Butyrev; Thorsten Edelhäußer; Christopher Mutschler (CoRR, 2019)

A Deep Learning Approach to Position Estimation from Channel Impulse Responses. - Arne Niitsoo; Thorsten Edelhäußer; Ernst Eberlein; Niels Hadaschik; Christopher Mutschler (Sensors, 2019)

Sick Moves! Motion Parameters as Indicators of Simulator Sickness. - Tobias Feigl; Daniel Roth 001; Stefan Gradl; Markus Wirth; Marc Erich Latoschik; Björn M. Eskofier; Michael Philippsen; Christopher Mutschler (IEEE Trans. Vis. Comput. Graph., 2019)

ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization. - Felix Ott 001; Tobias Feigl; Christoffer Löffler; Christopher Mutschler (CVPR Workshops, 2020)

Localization Limitations of ARCore, ARKit, and Hololens in Dynamic Large-scale Industry Environments. - Tobias Feigl; Andreas Porada; Steve Steiner; Christoffer Löffler; Christopher Mutschler; Michael Philippsen (VISIGRAPP (1: GRAPP), 2020)

NLOS Detection using UWB Channel Impulse Responses and Convolutional Neural Networks. - Maximilian Stahlke; Sebastian Kram; Christopher Mutschler; Thomas Mahr (ICL-GNSS, 2020)

Real-Time Gait Reconstruction For Virtual Reality Using a Single Sensor. - Tobias Feigl; Lisa Gruner; Christopher Mutschler; Daniel Roth 001 (ISMAR Adjunct, 2020)

A Sense of Quality for Augmented Reality Assisted Process Guidance. - Anes Redzepagic; Christoffer Löffler; Tobias Feigl; Christopher Mutschler (ISMAR Adjunct, 2020)

High-Speed Collision Avoidance using Deep Reinforcement Learning and Domain Randomization for Autonomous Vehicles. - Georgios D. Kontes; Daniel D. Scherer; Tim Nisslbeck; Janina Fischer; Christopher Mutschler (ITSC, 2020)

Automated Quality Assurance for Hand-Held Tools via Embedded Classification and AutoML. - Christoffer Löffler; Christian Nickel; Christopher Sobel; Daniel Dzibela; Jonathan Braat; Benjamin Gruhler; Philipp Woller; Nicolas Witt; Christopher Mutschler (ECML/PKDD (5), 2020)

IALE: Imitating Active Learner Ensembles. - Christoffer Löffler; Karthik Ayyalasomayajula; Sascha Riechel; Christopher Mutschler (CoRR, 2020)

The OnHW Dataset: Online Handwriting Recognition from IMU-Enhanced Ballpoint Pens with Machine Learning. - Felix Ott 001; Mohamad Wehbi; Tim Hamann; Jens Barth; Björn M. Eskofier; Christopher Mutschler (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020)

RNN-Aided Human Velocity Estimation from a Single IMU. - Tobias Feigl; Sebastian Kram; Philipp Woller; Ramiz H. Siddiqui; Michael Philippsen; Christopher Mutschler (Sensors, 2020)

Accuracy-Aware Compression of Channel Impulse Responses using Deep Learning. - Thomas Altstidl; Sebastian Kram; Oskar Herrmann; Maximilian Stahlke; Tobias Feigl; Christopher Mutschler (IPIN, 2021)

Robust ToA-Estimation using Convolutional Neural Networks on Randomized Channel Models. - Tobias Feigl; Ernst Eberlein; Sebastian Kram; Christopher Mutschler (IPIN, 2021)

Contact Tracing with the Exposure Notification Framework in the German Corona-Warn-App. - Steffen Meyer; Thomas Windisch; Adrian Perl; Daniel Dzibela; Robert Marzilger; Nicolas Witt; Justus Benzler; Göran Kirchner; Tobias Feigl; Christopher Mutschler (IPIN, 2021)

Can You Trust Your Autonomous Car? Interpretable and Verifiably Safe Reinforcement Learning. - Lukas M. Schmidt; Georgios D. Kontes; Axel Plinge; Christopher Mutschler (IV, 2021)

Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition. - Felix Ott 001; David Rügamer; Lucas Heublein; Bernd Bischl; Christopher Mutschler (ICPR Workshops (1), 2022)

Uncertainty-aware Evaluation of Time-series Classification for Online Handwriting Recognition with Domain Shift. - Andreas Klaß; Sven M. Lorenz; Martin W. Lauer-Schmaltz; David Rügamer; Bernd Bischl; Christopher Mutschler; Felix Ott 001 (STRL@IJCAI, 2022)

An Introduction to Multi-Agent Reinforcement Learning and Review of its Application to Autonomous Mobility. - Lukas M. Schmidt; Johanna Brosig; Axel Plinge; Bjoern M. Eskofier; Christopher Mutschler (ITSC, 2022)

How to Learn from Risk: Explicit Risk-Utility Reinforcement Learning for Efficient and Safe Driving Strategies. - Lukas M. Schmidt; Sebastian Rietsch; Axel Plinge; Bjoern M. Eskofier; Christopher Mutschler (ITSC, 2022)

Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift. - Felix Ott 001; David Rügamer; Lucas Heublein; Bernd Bischl; Christopher Mutschler (ACM Multimedia, 2022)

Incremental Data-Uploading for Full-Quantum Classification. - Maniraman Periyasamy; Nico Meyer; Christian Ufrecht; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (QCE, 2022)

Transfer Learning to adapt 5G AI-based Fingerprint Localization across Environments. - Maximilian Stahlke; Tobias Feigl; Mario Hernán Castañeda García; Richard A. Stirling-Gallacher; Jochen Seitz 002; Christopher Mutschler (VTC Spring, 2022)

Joint Classification and Trajectory Regression of Online Handwriting using a Multi-Task Learning Approach. - Felix Ott 001; David Rügamer; Lucas Heublein; Bernd Bischl; Christopher Mutschler (WACV, 2022)

Delay Estimation in Dense Multipath Environments using Time Series Segmentation. - Sebastian Kram; Christopher Kraus; Maximilian Stahlke; Tobias Feigl; Jörn Thielecke; Christopher Mutschler (WCNC, 2022)

Cross-Modal Common Representation Learning with Triplet Loss Functions. - Felix Ott 001; David Rügamer; Lucas Heublein; Bernd Bischl; Christopher Mutschler (CoRR, 2022)

Position Tracking using Likelihood Modeling of Channel Features with Gaussian Processes. - Sebastian Kram; Christopher Kraus; Tobias Feigl; Maximilian Stahlke; Jörg Robert; Christopher Mutschler (CoRR, 2022)

Deployment of Energy-Efficient Deep Learning Models on Cortex-M based Microcontrollers using Deep Compression. - Mark Deutel; Philipp Woller; Christopher Mutschler; Jürgen Teich (CoRR, 2022)

Driver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous Driving. - Sebastian Rietsch; Shih-Yuan Huang; Georgios D. Kontes; Axel Plinge; Christopher Mutschler (CoRR, 2022)

Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression. - Felix Ott 001; Nisha Lakshmana Raichur; David Rügamer; Tobias Feigl; Heiko Neumann; Bernd Bischl; Christopher Mutschler (CoRR, 2022)

Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approach. - Maximilian Stahlke; George Yammine; Tobias Feigl; Bjoern M. Eskofier; Christopher Mutschler (CoRR, 2022)

A Survey on Quantum Reinforcement Learning. - Nico Meyer; Christian Ufrecht; Maniraman Periyasamy; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (CoRR, 2022)

Benchmarking online sequence-to-sequence and character-based handwriting recognition from IMU-enhanced pens. - Felix Ott 001; David Rügamer; Lucas Heublein; Tim Hamann; Jens Barth; Bernd Bischl; Christopher Mutschler (Int. J. Document Anal. Recognit., 2022)

IALE: Imitating Active Learner Ensembles. - Christoffer Löffler; Christopher Mutschler (J. Mach. Learn. Res., 2022)

Deep Siamese Metric Learning: A Highly Scalable Approach to Searching Unordered Sets of Trajectories. - Christoffer Löffler; Luca Reeb; Daniel Dzibela; Robert Marzilger; Nicolas Witt; Björn M. Eskofier; Christopher Mutschler (ACM Trans. Intell. Syst. Technol., 2022)

Scaled and Translated Image Recognition (STIR). - Thomas Altstidl; An Nguyen; Leo Schwinn; Franz Köferl; Christopher Mutschler; Björn M. Eskofier; Dario Zanca (Zenodo, 2022)

Scaled and Translated Image Recognition (STIR) Source Data. - Thomas Altstidl; An Nguyen; Leo Schwinn; Franz Köferl; Christopher Mutschler; Björn M. Eskofier; Dario Zanca (Zenodo, 2022)

Quantum Policy Gradient Algorithm with Optimized Action Decoding. - Nico Meyer; Daniel D. Scherer; Axel Plinge; Christopher Mutschler; Michael J. Hartmann (ICML, 2023)

Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks. - Thomas Altstidl; An Nguyen; Leo Schwinn; Franz Köferl; Christopher Mutschler; Björn M. Eskofier; Dario Zanca (IJCNN, 2023)

Multipath Delay Estimation in Complex Environments using Transformer. - Jonathan Ott; Maximilian Stahlke; Sebastian Kram; Tobias Feigl; Christopher Mutschler (IPIN, 2023)

Uncertainty-based Fingerprinting Model Selection for Radio Localization. - Maximilian Stahlke; Tobias Feigl; Sebastian Kram; Bjoern M. Eskofier; Christopher Mutschler (IPIN, 2023)

Energy-efficient Deployment of Deep Learning Applications on Cortex-M based Microcontrollers using Deep Compression. - Mark Deutel; Philipp Woller; Christopher Mutschler; Jürgen Teich (MBMV, 2023)

μYOLO: Towards Single-Shot Object Detection on Microcontrollers. - Mark Deutel; Christopher Mutschler; Jürgen Teich (PKDD/ECML Workshops (5), 2023)

Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning. - Nico Meyer; Daniel D. Scherer; Axel Plinge; Christopher Mutschler; Michael J. Hartmann (QCE, 2023)

Workshop Summary: Quantum Machine Learning. - Volker Tresp; Steffen Udluft; Daniel Hein 001; Werner Hauptmann; Martin Leib; Christopher Mutschler; Daniel D. Scherer; Wolfgang Mauerer (QCE, 2023)

An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-Based Gradients. - Marco Wiedmann; Marc Hölle; Maniraman Periyasamy; Nico Meyer; Christian Ufrecht; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (QCE, 2023)

Efficient Beam Search for Initial Access Using Collaborative Filtering. - George Yammine; Georgios D. Kontes; Norbert Franke; Axel Plinge; Christopher Mutschler (WCNC, 2023)

Auxiliary Cross-Modal Representation Learning With Triplet Loss Functions for Online Handwriting Recognition. - Felix Ott 001; David Rügamer; Lucas Heublein; Bernd Bischl; Christopher Mutschler (IEEE Access, 2023)

Batch Quantum Reinforcement Learning. - Maniraman Periyasamy; Marc Hölle; Marco Wiedmann; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (CoRR, 2023)

Augmented Random Search for Multi-Objective Bayesian Optimization of Neural Networks. - Mark Deutel; Georgios D. Kontes; Christopher Mutschler; Jürgen Teich (CoRR, 2023)

C-MCTS: Safe Planning with Monte Carlo Tree Search. - Dinesh Parthasarathy; Georgios D. Kontes; Axel Plinge; Christopher Mutschler (CoRR, 2023)

Velocity-Based Channel Charting with Spatial Distribution Map Matching. - Maximilian Stahlke; George Yammine; Tobias Feigl; Bjoern M. Eskofier; Christopher Mutschler (CoRR, 2023)

Active Learning of Ordinal Embeddings: A User Study on Football Data. - Christoffer Löffler; Kion Fallah; Stefano Fenu; Dario Zanca; Björn M. Eskofier; Christopher John Rozell; Christopher Mutschler (Trans. Mach. Learn. Res., 2023)

Cutting multi-control quantum gates with ZX calculus. - Christian Ufrecht; Maniraman Periyasamy; Sebastian Rietsch; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (Quantum, 2023)

Uncovering instabilities in variational-quantum deep Q-networks. - Maja Franz; Lucas Wolf; Maniraman Periyasamy; Christian Ufrecht; Daniel D. Scherer; Axel Plinge; Christopher Mutschler; Wolfgang Mauerer (J. Frankl. Inst., 2023)

Few-Shot Learning with Uncertainty-Based Quadruplet Selection for Interference Classification in GNSS Data. - Felix Ott 001; Lucas Heublein; Nisha Lakshmana Raichur; Tobias Feigl; Jonathan Hansen; Alexander Rügamer; Christopher Mutschler (ICL-GNSS, 2024)

BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading. - Maniraman Periyasamy; Marc Hölle; Marco Wiedmann; Daniel D. Scherer; Axel Plinge; Christopher Mutschler (IJCNN, 2024)

Non-Line-of-Sight Detection for Radio Localization using Deep State Space Models. - Leon Brasseler; Maximilian Stahlke; Thomas Altstidl; Tobias Feigl; Christopher Mutschler (IPIN, 2024)

Radio Foundation Models: Pre-training Transformers for 5G-based Indoor Localization. - Jonathan Ott; Jonas Pirkl; Maximilian Stahlke; Tobias Feigl; Christopher Mutschler (IPIN, 2024)

Warm-Start Variational Quantum Policy Iteration. - Nico Meyer; Jakob Murauer; Alexander Popov; Christian Ufrecht; Axel Plinge; Christopher Mutschler; Daniel D. Scherer (QCE, 2024)

Comprehensive Library of Variational LSE Solvers. - Nico Meyer; Martin Röhn; Jakob Murauer; Axel Plinge; Christopher Mutschler; Daniel D. Scherer (QCE, 2024)

Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks. - Nico Meyer; Christian Ufrecht; Maniraman Periyasamy; Axel Plinge; Christopher Mutschler; Daniel D. Scherer; Andreas Maier 001 (QCE, 2024)

Guided-SPSA: Simultaneous Perturbation Stochastic Approximation Assisted by the Parameter Shift Rule. - Maniraman Periyasamy; Axel Plinge; Christopher Mutschler; Daniel D. Scherer; Wolfgang Mauerer (QCE, 2024)

Unitary Synthesis of Clifford+T Circuits with Reinforcement Learning. - Sebastian Rietsch; Abhishek Y. Dubey; Christian Ufrecht; Maniraman Periyasamy; Axel Plinge; Christopher Mutschler; Daniel D. Scherer (QCE, 2024)

SCIM MILQ: An HPC Quantum Scheduler. - Philipp Seitz; Manuel Geiger; Christian Ufrecht; Axel Plinge; Christopher Mutschler; Daniel D. Scherer; Christian B. Mendl (QCE, 2024)

microYOLO: Towards Single-Shot Object Detection on Microcontrollers. - Mark Deutel; Christopher Mutschler; Jürgen Teich (CoRR, 2024)

Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification. - Saurabh Sampatrao Gaikwad; Lucas Heublein; Nisha Lakshmana Raichur; Tobias Feigl; Christopher Mutschler; Felix Ott 001 (CoRR, 2024)

Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization. - Nico Meyer; Julian Berberich; Christopher Mutschler; Daniel D. Scherer (CoRR, 2024)

Fusing structure from motion and simulation-augmented pose regression from optical flow for challenging indoor environments. - Felix Ott 001; Lucas Heublein; David Rügamer; Bernd Bischl; Christopher Mutschler (J. Vis. Commun. Image Represent., 2024)

Reinforcement Learning for Node Selection in Branch-and-Bound. - Alexander Mattick; Christopher Mutschler (Trans. Mach. Learn. Res., 2024)

Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML (Code). - Mark Deutel; Georgios Kontes; Christopher Mutschler; Jürgen Teich (Zenodo, 2024)

Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization. - Lucas Heublein; Tobias Feigl; Thorsten Nowak; Alexander Rügamer; Christopher Mutschler; Felix Ott 001 (ICL-GNSS, 2025)

Vae-Based Feature Disentanglement for Data Augmentation and Compression in Generalized Gnss Interference Classification. - Lucas Heublein; Simon Kocher; Tobias Feigl; Alexander Rügamer; Christopher Mutschler; Felix Ott 001 (ICL-GNSS, 2025)

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization. - Nisha Lakshmana Raichur; Lucas Heublein; Christopher Mutschler; Felix Ott 001 (ICL-GNSS, 2025)

Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification. - Nishant S. Gaikwad; Lucas Heublein; Nisha Lakshmana Raichur; Tobias Feigl; Christopher Mutschler; Felix Ott 001 (NOMS, 2025)

PDRNN: Modular Data-driven Pedestrian Dead Reckoning on Loosely Coupled Radio- and Inertial-Signalstreams. - Peter Bauer; Andreas Porada; Felix Ott 001; Christopher Mutschler; Tobias Feigl (PLANS, 2025)

Exploitation of Hidden Context in Dynamic Movement Forecasting: A Neural Network Journey from Recurrent to Graph Neural Networks and General Purpose Transformers. - Lukas Schelenz; Shobha Rajanna; Denis Gosalci; Lucas Heublein; Jonas Pirkl; Jonathan Ott; Felix Ott 001; Christopher Mutschler; Tobias Feigl (PLANS, 2025)

GenAI for Energy-Efficient and Interference-Aware Compressed Sensing of GNSS Signals on a Google Edge TPU. - Thorben Wegner; Lucas Heublein; Tobias Feigl; Felix Ott 001; Christopher Mutschler; Alexander Rügamer (PLANS, 2025)

Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning. - Nisha Lakshmana Raichur; Lucas Heublein; Tobias Feigl; Alexander Rügamer; Christopher Mutschler; Felix Ott 001 (Trans. Mach. Learn. Res., 2025)

Benchmarking Quantum Reinforcement Learning. - Nico Meyer; Christian Ufrecht; George Yammine; Georgios D. Kontes; Christopher Mutschler; Daniel D. Scherer (CoRR, 2025)

Optimizing Quantum Circuits via ZX Diagrams using Reinforcement Learning and Graph Neural Networks. - Alexander Mattick; Maniraman Periyasamy; Christian Ufrecht; Abhishek Y. Dubey; Christopher Mutschler; Axel Plinge; Daniel D. Scherer (CoRR, 2025)

On-Device Training of Fully Quantized Deep Neural Networks on Cortex-M Microcontrollers. - Mark Deutel; Frank Hannig; Christopher Mutschler; Jürgen Teich (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

Simplicity is Key: An Unsupervised Pretraining Approach for Sparse Radio Channels. - Jonathan Ott; Maximilian Stahlke; Tobias Feigl; Bjoern M. Eskofier; Christopher Mutschler (CoRR, 2025)

Position Paper: Rethinking AI/ML for Air Interface in Wireless Networks. - Georgios D. Kontes; Diomidis S. Michalopoulos; Birendra Ghimire; Christopher Mutschler (CoRR, 2025)

Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction. - Nico Meyer; Christopher Mutschler; Andreas K. Maier; Daniel D. Scherer (CoRR, 2025)

Attention-Based Fusion of IQ and FFT Spectrograms with AoA Features for GNSS Jammer Localization. - Lucas Heublein; Christian Wielenberg; Thorsten Nowak; Tobias Feigl; Christopher Mutschler; Felix Ott 001 (CoRR, 2025)

Don't get me wrong: How to apply deep visual interpretations to time series. - Christoffer Löffler; Wei-Cheng Lai; Dario Zanca; Lukas Schmidt; Björn M. Eskofier; Christopher Mutschler (Appl. Intell., 2025)