Publikationen

Fraunhofer-Allianz Big Data und Künstliche Intelligenz (2025):

Jenseits von Text und Bild - Generative KI für vielfältige Datenwelten: Praxisnahe Einblicke und innovative Anwendungsbeispiele zur Erschließung komplexer Unternehmensdaten 

Whitepaper, Fraunhofer Verlag

Lucas Heublein, Thorsten Nowak, Tobias Feigl, Jaspar Pahl, and Felix Ott (2025):

GNSS Jammer Direction Finding in Dynamic Scenarios Using an Inertial-based Multi-Antenna System

DGON Inertial Sensors and Applications (ISA)

Jain, P., Kasper, M., Köber, G., Amft, O., Plinge, A., & Seuss, D. (2025):

Pareto optimal benchmarking of AI models on ARM Cortex processors for sustainable embedded systems.

European Conference on EDGE AI Technologies and Applications (EEAI 2025).

Brolich, N., Geis, S., Kasper, M., Barnhill, A., Plinge, A., & Seuss, D. (2025):

Investigating target class influence on neural network compressibility for energy-autonomous avian monitoring.

In: European Conference on EDGE AI Technologies and Applications (EEAI 2025).

Wiedmann, M., Periyasamy, M., Scherer, D. (2025):

Fourier Analysis of Variational Quantum Circuits for Supervised Learning.

IEEE QCE 2025.

Periyasamy, M., Ufrecht, C., Scherer, D., Mauerer, W. (2025):

CutReg: A loss regularizer for enhancing the scalability of QML via adaptive circuit cutting. 

IEEE QML@QCE Workshop 2025.

Geißler, F., Stopfer, E., Ufrecht, C., Meyer, N., Scherer, D., Wagner, F., and others (2025):

BenchQC – Scalable and modular benchmarking of industrial quantum computing applications.

QUEST-IS 2025.

Marchl, A., Kasper, M. Geis, S., Deutel, M., Plinge A., Seuß, D. (2025):

Anomaly Detection on the Edge for Quality Inspection. 

AI in Production Workshop at KI2025

Mattick, A., Sturm, L., Müller, F., Loftus, S., Asif, H., Plinge, A., Mutschler, C., Pahl, J., Seuß, D., & Göttl, Q. (2025):

Cross-Attentive Bipartite Graph Reinforcement Learning for Prize-Collecting Job Shop Scheduling 

AI in Production Workshop at KI2025

Lucas Heublein, Christian Wielenberg, Thorsten Nowak, Tobias Feigl, Christopher Mutschler, and Felix Ott (2025):

Attention-Based Fusion of IQ and FFT Spectrograms with AoA Features for GNSS Jammer Localization

IEEE Radar Conference

Deutel, M., Plinge, A., Seuß, D., Mutschler, C., Hannig, F., & Teich, J. (2025): 

Unsupervised learning of variational autoencoders on Cortex-M microcontrollers.

IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC 2025), Singapore

Ott, J., Stahlke, M., Feigl, T., Eskofier, B. M., & Mutschler, C. (2025):

Simplicity is Key: An Unsupervised Pretraining Approach for Sparse Radio Channels. 

International Conference on Machine Learning (ICML ML4Wireless Workshop), Vancouver, BC, Canada

Meyer, N., Ufrecht, C., Yammine, G., Kontes, G., Mutschler, C., & Scherer, D. D. (2025):

Benchmarking Quantum Reinforcement Learning. 

International Conference on Machine Learning (ICML), Vancouver, BC, Canada.

Deutel, M., Kontes, G., Mutschler, C., & Teich, J. (2025):

Multi-Objective Bayesian Optimization with Reinforcement Learning for Edge Deployment of DNNs on Microcontrollers.

Paper presentation at Genetic and Evolutionary Computation Conference (GECCO), Málaga, ES.

Brans, P. & Witt, N. (2025):

Fraunhofer IIS Walks the Line for Edge AI

In: EE Times Europe Magazine

Lucas Heublein, Tobias Feigel, Thorsten Nowak, Alexander Rügamer, Christopher Mutschler, Felix Ott (2025):

Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization

Intl. Conf. on Localization and GNSS (ICL-GNSS)

Nisha L. Raichur, Lucas Heublein, Christopher Mutschler, Felix Ott (2025):

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization

Intl. Conf. on Localization and GNSS (ICL-GNSS)

Manjunath, H., Heublein, L., Feigl, T., & Ott, F. (2025):

Multimodal-to-Text Prompt Engineering in Large Language Models Using Feature Embeddings for GNSS Interference Characterization

In: IEEE Wireless Communications and Networking Conference (WCNC), March 2025, Milan, Italy

Gaikwad, N. S., Heublein, L., Raichur, N. L., Feigl, T., Mutschler, C., & Ott, F. (2024):

Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification

In: arXiv preprint arXiv:2410.15681

Heublein, L., Feigl, T., Rügamer, A., & Ott, F. (2024):

Achieving Generalization in Orchestrating GNSS Interference Monitoring Stations Through Pseudo-Labeling

In: DGON Positioning and Navigation for Intelligent Transport Systems (POSNAV), October 2024

Heublein, L., Feigl, T., Nowak, T., Rügamer, A., Mutschler, C., & Ott, F. (2024):

Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization 

In: IEEE Intl. Conf. on Localization and GNSS (ICL-GNSS), June 2025, Rome, Italy

Mutschler, C., Münzenmayer, C., Uhlmann, N., & Martin, A (2024): 

Unlocking Artificial Intelligence: From Theory to Applications

In: Springer

Ott, F., Heublein, L., Rügamer, D., Bischl, B., & Mutschler, C. (2024):

Fusing structure from motion and simulation-augmented pose regression from optical flow for challenging indoor environments

In: Journal of Visual Communication and Image Representation, 103, 104256

Raichur, N. L., Heublein, L., Feigl, T., Rügamer, A., Mutschler, C., & Ott, F. (2024):

Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning

In: Transactions on Machine Learning Research (TMLR), March 2025, https://openreview.net/forum?id=dNWaTuKV9M

Ott, J., Pirkl, J., Stahlke, M., Feigl, T., & Mutschler, C. (2024):

Radio Foundation Models: Pre-training Transformers for 5G-based Indoor Localization

In: 2024 14th International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-6)

Göttl, Q., Asif, H., Mattick, A., Marzilger, R., & Plinge, A. (2024):

Automated Design in Hybrid Action Spaces by Reinforcement Learning and Differential Evolution

In: German Conference on Artificial Intelligence (Künstliche Intelligenz) (pp. 292-299)

Ott, F., Heublein, L., Raichur, N. L., Feigl, T., Hansen, J., Rügamer, A., & Mutschler, C. (2024):

Few-shot learning with uncertainty-based quadruplet selection for interference classification in GNSS data

In: 2024 International Conference on Localization and GNSS (ICL-GNSS) (pp. 1-7)

Heublein, L., Raichur, N. L., Feigl, T., Brieger, T., Heuer, F., Asbach, L., ... & Ott, F. (2024):

Evaluation of (Un-) Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies

In: Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024) (pp. 1260-1293)

Ott, F., Heublein, L., & Feigl, T. (2024):

Research Avenues for GNSS Interference Classification Robustness: Domain Adaptation, Continual Learning & Federated Learning

In: ECML PKDD Industry Track

Witt, N., Deutel, M., Schubert, J., Sobel, C., & Woller, P. (2024)

Energy-Efficient AI on the Edge

In: Unlocking Artificial Intelligence: From Theory to Applications (pp. 359-380)

Deutel, M., Hannig, F., Mutschler, C., & Teich, J (2024):

Fused-Layer CNNs for Memory-Efficient Inference on Microcontrollers

In: Workshop on Machine Learning and Compression, NeurIPS 2024

Deutel, M., Hannig, F., Mutschler, C., & Teich, J. (2024):

On-Device Training of Fully Quantized Deep Neural Networks on Cortex-M Microcontrollers

In: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2024

Deutel, M., Mutschler, C., & Teich, J. (2024):

microYOLO: Towards Single-Shot Object Detection on Microcontrollers

In: arXiv preprint arXiv:2408.15865.

Herzog, B., Schubert, J., Rheinfels, T., Nickel, C., & Hönig, T. (2024):

GreenPipe: Energy-Efficient Data-Processing Pipelines for Resource-Constrained Systems.

In: Proceedings of the 21st International Conference on Embedded Wireless Systems and Networks (EWSN'24), ACM

Periyasamy, M., Plinge, A., Mutschler, C., Scherer, D. D., & Mauerer, W. (2024):

Guided-spsa: Simultaneous perturbation stochastic approximation assisted by the parameter shift rule

In: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 1, pp. 1504-1515)

Rietsch, S., Dubey, A. Y., Ufrecht, C., Periyasamy, M., Plinge, A., Mutschler, C., & Scherer, D. D. (2024):

Unitary synthesis of clifford+t circuits with reinforcement learning

In: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 1, pp. 824-835)

Meyer, N., Murauer, J., Popov, A., Ufrecht, C., Plinge, A., Mutschler, C., & Scherer, D. D. (2024):

Warm-start variational quantum policy iteration

In: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 1, pp. 1458-1466)

Meyer, N., Ufrecht, C., Periyasamy, M., Plinge, A., Mutschler, C., Scherer, D. D., & Maier, A. (2024):

Qiskit-torch-module: Fast prototyping of quantum neural networks

In: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 1, pp. 817-823)

Meyer, N., Röhn, M., Murauer, J., Plinge, A., Mutschler, C., & Scherer, D. D. (2024):

Comprehensive Library of Variational LSE Solvers

In: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 2, pp. 1-4)

Seitz, P., Geiger, M., Ufrecht, C., Plinge, A., Mutschler, C., Scherer, D. D., & Mendl, C. B. (2024):

SCIM MILQ: an HPC quantum scheduler

In: 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 2, pp. 292-298)

Richter, M., Dubey, A. Y., Plinge, A., Mutschler, C., Scherer, D. D., & Hartmann, M. J. (2024):

Quantum Wasserstein Compilation: Unitary Compilation using the Quantum Earth Mover's Distance

In: arXiv preprint arXiv:2409.05849

Yammine, G., Kontes, G., Franke, N., Plinge, A., & Mutschler, C. (2023):

Efficient Beam Search for Initial Access Using Collaborative Filtering

In: 2023 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1-6)

Ufrecht, C., Periyasamy, M., Rietsch, S., Scherer, D. D., Plinge, A., & Mutschler, C. (2023):

Cutting multi-control quantum gates with ZX calculus

In: Quantum, 7, 1147

Meyer, N., Scherer, D. D., Plinge, A., Mutschler, C., & Hartmann, M. J. (2023):

Quantum natural policy gradients: Towards sample-efficient reinforcement learning

In: 2023 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 2, pp. 36-41)

Wiedmann, M., Hölle, M., Periyasamy, M., Meyer, N., Ufrecht, C., Scherer, D. D., ... & Mutschler, C. (2023):

An empirical comparison of optimizers for quantum machine learning with spsa-based gradients

In: 2023 IEEE International Conference on Quantum Computing and Engineering (QCE) (Vol. 1, pp. 450-456)

Franz, M., Wolf, L., Periyasamy, M., Ufrecht, C., Scherer, D. D., Plinge, A., ... & Mauerer, W. (2023):

Uncovering instabilities in variational-quantum deep q-networks

In: Journal of The Franklin Institute, 360(17), pp. 13822-13844

Meyer, N., Scherer, D., Plinge, A., Mutschler, C., & Hartmann, M. (2023):

Quantum policy gradient algorithm with optimized action decoding

In: International Conference on Machine Learning (pp. 24592-24613)

Rietsch, S., Huang, S. Y., Kontes, G., Plinge, A., & Mutschler, C. (2022)

Driver dojo: A benchmark for generalizable reinforcement learning for autonomous driving

In: arXiv preprint arXiv:2207.11432

Landgraf, D., Völz, A., Kontes, G., Mutschler, C., & Graichen, K. (2022):

Hierarchical learning for model predictive collision avoidance

In: IFAC-PapersOnLine, 55(20), 355-360

Schmidt, L. M., Brosig, J., Plinge, A., Eskofier, B. M., & Mutschler, C. (2022):

An introduction to multi-agent reinforcement learning and review of its application to autonomous mobility

In: 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 1342-1349)

Schmidt, L. M., Rietsch, S., Plinge, A., Eskofier, B. M., & Mutschler, C. (2022):

How to learn from risk: Explicit risk-utility reinforcement learning for efficient and safe driving strategies

In: 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 1913-1920)

Periyasamy, M., Meyer, N., Ufrecht, C., Scherer, D. D., Plinge, A., & Mutschler, C. (2022):

Incremental data-uploading for full-quantum classification

In: 2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (pp. 31-37)

Meyer, N., Ufrecht, C., Periyasamy, M., Scherer, D. D., Plinge, A., & Mutschler, C. (2022):

A survey on quantum reinforcement learning

In: arXiv preprint arXiv:2211.03464

Adler, R., Bunte, A., Burton, S., Großmann, J., Jaschke, A., Kleen, P., ... & Wrobel, S. (2022):

Deutsche Normungsroadmap Künstliche Intelligenz

In: Fraunhofer Publica

Ott, F., Rügamer, D., Heublein, L., Bischl, B., & Mutschler, C. (2022):

Joint classification and trajectory regression of online handwriting using a multi-task learning approach

In: Proceedings of the IEEE/CVF winter conference on applications of computer vision (pp. 266-276)

Reeb, L. (2022):

Searching for Soccer Scenes using Siamese Neural Networks

In: Towards Data Science 2022

Löffler, C., & Mutschler, C. (2022):

IALE: imitating active learner ensembles

In: Journal of Machine Learning Research, 23(107), 1-29

Lukcin, I., Duong, P. B., Dietmayer, K., Ali, S. U., Kram, S., Seitz, J., & Felber, W. (2021):

A Combined Ray Tracing Simulation Environment for Hybrid 5G and GNSS Positioning

In: ICL-GNSS 2021 WiP Proceedings

Blauberger, P., Marzilger, R., & Lames, M. (2021):

Validation of player and ball tracking with a local positioning system

In: Sensors, 21(4), 1465

Potortì, F., Torres-Sospedra, J., Quezada-Gaibor, D., Jiménez, A. R., Seco, F., Pérez-Navarro, A., ... & Oh, H. L. (2021):

Off-line evaluation of indoor positioning systems in different scenarios: The experiences from IPIN 2020 competition

In: IEEE Sensors Journal, 22(6), 5011-5054

Stahlke, M., Kram, S., Ott, F., Feigl, T., & Mutschler, C. (2021):

Estimating TOA reliability with variational autoencoders

In: IEEE Sensors Journal, 22(6), 5133-5140

Schmidt, L. M., Kontes, G., Plinge, A., & Mutschler, C. (2021):

Can you trust your autonomous car? interpretable and verifiably safe reinforcement learning

In: 2021 IEEE Intelligent Vehicles Symposium (IV) (pp. 171-178)

Löffler, C., Reeb, L., Dzibela, D., Marzilger, R., Witt, N., Eskofier, B. M., & Mutschler, C. (2021):

Deep siamese metric learning: A highly scalable approach to searching unordered sets of trajectories

In: ACM Transactions on Intelligent Systems and Technology (TIST), 13(1), 1-23

Löffler, C., Nickel, C., Sobel, C., Dzibela, D., Braat, J., Gruhler, B., ... & Mutschler, C. (2021):

Automated quality assurance for hand-held tools via embedded classification and AutoML

In: Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V (pp. 532-535)

Ott, F., Wehbi, M., Hamann, T., Barth, J., Eskofier, B., & Mutschler, C. (2020):

The onhw dataset: Online handwriting recognition from imu-enhanced ballpoint pens with machine learning

In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(3), 1-20

Feigl, T., Kram, S., Woller, P., Siddiqui, R. H., Philippsen, M., & Mutschler, C. (2020):

RNN-aided human velocity estimation from a single IMU

In: Sensors, 20(13), 3656

Ott, F., Feigl, T., Loffler, C., & Mutschler, C. (2020):

ViPR: visual-odometry-aided pose regression for 6DoF camera localization

In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (pp. 42-43)

Feigl, T., Porada, A., Steiner, S., Löffler, C., Mutschler, C., & Philippsen, M. (2020):

Localization Limitations of ARCore, ARKit, and Hololens in Dynamic Large-scale Industry Environments

In: VISIGRAPP (1: GRAPP) (pp. 307-318)

Stahlke, M., Kram, S., Mutschler, C., & Mahr, T. (2020):

NLOS detection using UWB channel impulse responses and convolutional neural networks

In: 2020 International Conference on Localization and GNSS (ICL-GNSS) (pp. 1-6)

Feigl, T., Gruner, L., Mutschler, C., & Roth, D. (2020):

Real-time gait reconstruction for virtual reality using a single sensor

In: 2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) (pp. 84-89)

Redžepagić, A., Löffler, C., Feigl, T., & Mutschler, C. (2020):

A sense of quality for augmented reality assisted process guidance

In: 2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) (pp. 129-134)

Kontes, G. D., Scherer, D. D., Nisslbeck, T., Fischer, J., & Mutschler, C. (2020):

High-speed collision avoidance using deep reinforcement learning and domain randomization for autonomous vehicles

In: 2020 IEEE 23rd international conference on Intelligent Transportation Systems (ITSC) (pp. 1-8)

Mishra, A., Löffler, C., & Plinge, A. (2020):

Recipes for Post-training Quantization of Deep Neural Networks

In: Workshop on Energy Efficient Machine Learning and Cognitive Computing; 2020 Virtual 

Niitsoo, A., Edelhäußer, T., Eberlein, E., Hadaschik, N., & Mutschler, C. (2019):

A deep learning approach to position estimation from channel impulse responses

In: Sensors, 19(5), 1064

Feigl, T., Roth, D., Gradl, S., Wirth, M., Latoschik, M. E., Eskofier, B. M., ... & Mutschler, C. (2019):

Sick moves! motion parameters as indicators of simulator sickness

In: IEEE transactions on visualization and computer graphics, 25(11), 3146-3157

Feigl, T., Kram, S., Woller, P., Siddiqui, R. H., Philippsen, M., & Mutschler, C. (2019):

A bidirectional LSTM for estimating dynamic human velocities from a single IMU

In: 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-8)

Feigl, T., Kram, S., Woller, P., Siddiqui, R. H., Philippsen, M., & Mutschler, C. (2019):

A bidirectional LSTM for estimating dynamic human velocities from a single IMU

In: Computer Vision Foundation (CVF) (Eds.), Joint Workshop on Long-Term Visual Localization, Visual Odometry and Geometric and Learning-based SLAM (pp. 42-43)

Butyrev, L., Edelhäußer, T., & Mutschler, C. (2019):

Deep reinforcement learning for motion planning of mobile robots

In: arXiv preprint arXiv:1912.09260

Kram, S., Stahlke, M., Feigl, T., Seitz, J., & Thielecke, J. (2019):

UWB channel impulse responses for positioning in complex environments: A detailed feature analysis

In: Sensors, 19(24), 5547

Ghimire, B., Seitz, J., & Mutschler, C. (2018):

Indoor positioning using OFDM-based visible light communication system

In: 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-8)

Löffler, C., Riechel, S., Fischer, J., & Mutschler, C. (2018):

Evaluation criteria for inside-out indoor positioning systems based on machine learning

In: 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-8)

Niitsoo, A., Edelhäußer, T., & Mutschler, C. (2018):

Convolutional neural networks for position estimation in tdoa-based locating systems

In: 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-8)

Nowak, T., Hartmann, M., Thielecke, J., Hadaschik, N., & Mutschler, C. (2018):

Super-resolution in RSS-based direction-of-arrival estimation

In: 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1-8)

Feigl, T., Mutschler, C., & Philippsen, M. (2018):

Supervised learning for yaw orientation estimation

In: 2018 international conference on indoor positioning and indoor navigation (IPIN) (pp. 206-212)

Feigl, T., Nowak, T., Philippsen, M., Edelhäußer, T., & Mutschler, C. (2018):

Recurrent neural networks on drifting time-of-flight measurements

In: 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 206-212)

Feigl, T., Mutschler, C., & Philippsen, M. (2018):

Human compensation strategies for orientation drifts

In: 2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 409-414)

Feigl, T., Mutschler, C., & Philippsen, M. (2018):

Head-to-body-pose classification in no-pose VR tracking systems

In: 2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 1-2)

Roth, D., Klelnbeck, C., Feigl, T., Mutschler, C., & Latoschik, M. E. (2018):

Beyond replication: Augmenting social behaviors in multi-user virtual realities

In: 2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (pp. 215-222)

Lugrin, J. L., Kern, F., Schmidt, R., Kleinbeck, C., Roth, D., Daxer, C., ... & Latoschik, M. E. (2018):

A location-based VR museum

In: 2018 10Th international conference on virtual worlds and games for serious applications (VS-games) (pp. 1-2)

Gorse, L., Löffler, C., Mutschler, C., & Philippsen, M. (2018):

Optical camera communication for active marker identification in camera-based positioning systems

In: 2018 15th Workshop on Positioning, Navigation and Communications (WPNC) (pp. 1-6)

Roth, D., Kleinbeck, C., Feigl, T., Mutschler, C., & Latoschik, M. E. (2017):

Social augmentations in multi-user virtual reality: A virtual museum experience

In: 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct) (pp. 42-43)

Feigl, T., Kõre, E., Mutschler, C., & Philippsen, M. (2017):

Acoustical manipulation for redirected walking

In: Proceedings of the 23rd ACM symposium on virtual reality software and technology (pp. 1-2)

Gradl, S., Eskofier, B. M., Eskofier, D., Mutschler, C., & Otto, S. (2016):

Virtual and augmented reality in sports: an overview and acceptance study

In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (pp. 885-888)

Alawieh, M., Hadaschik, N., Franke, N., & Mutschler, C. (2016):

Inter-satellite ranging in the low earth orbit

In: 2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP) (pp. 1-6)

Sackenreuter, B., Hadaschik, N., Faßbinder, M., & Mutschler, C. (2016):

Low-complexity PDoA-based localization

In: 2016 international conference on indoor positioning and indoor navigation (IPIN) (pp. 1-6)

Löffler, C., Mutschler, C., & Philippsen, M. (2015):

Approximative event processing on sensor data streams (Best Poster and Demostration Award)

In: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems (pp. 360-363)

Mutschler, C., & Philippsen, M. (2014):

Adaptive speculative processing of out-of-order event streams

In: ACM Transactions on Internet Technology (TOIT), 14(1), 1-24

Mutschler, C. (2014):

Latency minimization of order-preserving distributed event-based systems

In: Dissertation. Dr. Hut Verlag. 229 Seiten. ISBN 978-3-8439-1472-7

Mutschler, C., Löffler, C., Witt, N., Edelhäußer, T., & Philippsen, M. (2014):

Predictive load management in smart grid environments

In: Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems (pp. 282-287)

Mutschler, C., Ziekow, H., & Jerzak, Z. (2013):

The DEBS 2013 grand challenge

In: Proceedings of the 7th ACM international conference on Distributed event-based systems (pp. 289-294)

Mutschler, C., Witt, N., & Philippsen, M. (2013):

Demo: do event-based systems have a passion for sports?

In: Proceedings of the 7th ACM international conference on Distributed event-based systems (pp. 331-332)

Mutschler, C., & Philippsen, M. (2013):

Reliable speculative processing of out-of-order event streams in generic publish/subscribe middlewares

In: Proceedings of the 7th ACM international conference on Distributed event-based systems (pp. 147-158)

Löffler, C., Mutschler, C., & Philippsen, M. (2013):

Evolutionary algorithms that use runtime migration of detector processes to reduce latency in event-based systems

In: 2013 NASA/ESA Conference on Adaptive Hardware and Systems (AHS-2013) (pp. 31-38)

Mutschler, C., & Philippsen, M. (2013):

Dynamic Low-Latency Distributed Event Processing of Sensor Data Streams

In: GI (Hrsg.): Proceedings of the 25th Workshop on Parallel Systems and Algorithms (PARS 2013) (25th Workshop on Parallel Systems and Algorithms (PARS 2013), Erlangen, Germany)

Mutschler, C., & Philippsen, M. (2013):

Runtime migration of stateful event detectors with low-latency ordering constraints

In: 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops) (pp. 609-614)

Mutschler, C., & Philippsen, M. (2013):

Distributed low-latency out-of-order event processing for high data rate sensor streams

In: 2013 IEEE 27th International Symposium on Parallel and Distributed Processing (pp. 1133-1144)

Mutschler, C., & Philippsen, M. (2012):

Learning event detection rules with noise hidden markov models

In: 2012 NASA/ESA Conference on Adaptive Hardware and Systems (AHS) (pp. 159-166)