Applied Machine Learning
The Applied Machine Learning group aims to develop and apply novel Machine Learning methods for real-world applications. Emerging digitalization allows companies from different fields of industry to produce and collect data from various resources. This is realized by technologies like the Internet of Things (IoT), cyber-physical systems and cloud-computing. To effectively handle this big data, Deep Learning and Signal Processing techniques are needed to provide powerful and promising solutions.
Group Head
Group Members
Students
If you are interested in writing a Bachelor’s or Master’s thesis in our group, please check the lab’s Student Theses and Jobs.
- Huang Haiting
Comparing Performance and Transparency of Multimodal Foundation Models in Healthcare
- Nils Steinlein
The creation and evaluation of a video-based polar bear Re-Identification dataset on current Re-ID methods - Sara Zarifi
Lynx Re-Identification from Camera Trap Images in the Wild
Projects
- Applications of Deep Learning for Signal Analysis
- Development of neural networks and machine learning algorithms for online handwriting recognition
- Tracking in the Deutsche Museum Nürnberg
- Machine Learning For Predictive Analytics
- Holistic customer-oriented service optimization for fleet availability
- Tool Tracking
- Digital Twin of Rheuma
- Machine Learning for CT-Detector Production
- VERA (Video-based Re-Identification for Animals)
- TegrityHub
- Multimodal Machine Learning for Decision Support Systems
- Biologically-inspired self-supervised systems
- Automated German Crossword Resolution
- TEF-Health
- TEAM-X
- Privacy-Preserving Analysis of Distributed Medical Data
- SELFCURE: Evolutionary and cognitive processes underlying self-medication of immune-challenged bats
2025
- Raab R., Berrang P., Gerhart P., Schröder D.:
SoK: Descriptive Statistics Under Local Differential Privacy
In: Proceedings on Privacy Enhancing Technologies 2025 (2025), p. 118-149
ISSN: 2299-0984
DOI: 10.56553/popets-2025-0008
BibTeX: Download
2024
- Abdelaal M., Yayak AB., Klede K., Schöning H.:
ReClean: Reinforcement Learning for Automated Data Cleaning in ML Pipelines
3rd International Workshop on Databases and Machine Learning (Utrecht, 13. May 2024 - 13. May 2024)
Open Access: https://www.wis.ewi.tudelft.nl/assets/files/dbml2024/DBML24_paper_11.pdf
URL: https://www.wis.ewi.tudelft.nl/assets/files/dbml2024/DBML24_paper_11.pdf
BibTeX: Download - Altstidl TR., Dobre D., Kosmala A., Eskofier B., Gidel G., Schwinn L.:
On the Scalability of Certified Adversarial Robustness with Generated Data
Neural Information Processing Systems (NeurIPS) (Vancouver, BC, Canada, 9. December 2024 - 15. December 2024)
In: Advances in Neural Information Processing Systems 37 2024
Open Access: https://proceedings.neurips.cc/paper_files/paper/2024/file/b96ce7d38339874a8704e8895f743284-Paper-Conference.pdf
URL: https://proceedings.neurips.cc/paper_files/paper/2024/file/b96ce7d38339874a8704e8895f743284-Paper-Conference.pdf
BibTeX: Download - Brasseler L., Stahlke M., Altstidl TR., Feigl T., Mutschler C.:
Non-Line-of-Sight Detection for Radio Localization using Deep State Space Models
14th International Conference on Indoor Positioning and Indoor Navigation (IPIN) (Hong Kong, 14. October 2024 - 17. October 2024)
In: The fourteenth International Conference on Indoor Positioning and Indoor Navigation 2024 (IPIN 2024) 2024
BibTeX: Download - Dietz S., Altstidl TR., Zanca D., Eskofier B., Nguyen A.:
How Intermodal Interaction Affects the Performance of Deep Multimodal Fusion for Mixed-Type Time Series
International Joint Conference on Neural Networks (IJCNN) (Yokohama, 30. June 2024 - 5. July 2024)
DOI: 10.1109/IJCNN60899.2024.10650421
URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10650421
BibTeX: Download - Dumbach P.:
Adoption of Artificial Intelligence in Industry and Politics: An Analysis Based on Web Mining and Case Studies across Diverse Data Sources (Dissertation, 2024)
URL: https://open.fau.de/handle/openfau/31160
BibTeX: Download - Klede K., Altstidl TR., Zanca D., Eskofier B.:
The Impact of Random Models on Standardized Clustering Similarity
In: IEEE Access (2024)
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3507133
URL: https://ieeexplore.ieee.org/document/10769363
BibTeX: Download - Küderle A., Ullrich M., Roth N., Ollenschläger M., Ibrahim A., Moradi H., Richer R., Seifer AK., Zürl M., Simpetru R., Herzer L., Prossel D., Kluge F., Eskofier B.:
Gaitmap – An Open Ecosystem for IMU-based Human Gait Analysis and Algorithm Benchmarking
In: IEEE Open Journal of Engineering in Medicine and Biology (2024), p. 1-10
ISSN: 2644-1276
DOI: 10.1109/OJEMB.2024.3356791
BibTeX: Download - Nieth B., Altstidl TR., Schwinn L., Eskofier B.:
Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation
International Conference on Machine Learning 2024 DMLR Workshop: Data-centric Machine Learning Research (Wien, 26. July 2024 - 27. July 2024)
DOI: 10.48550/arXiv.2406.13283
BibTeX: Download - Roider J., Nguyen A., Zanca D., Eskofier B.:
Assessing the Performance of Remaining Time Prediction Methods for Business Processes
In: IEEE Access (2024), p. 1-19
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3459648
URL: https://ieeexplore.ieee.org/abstract/document/10679137
BibTeX: Download - Roider J., Wang W., Zanca D., Matzner M., Eskofier B.:
Predictions in Predictive Process Monitoring with Previously Unseen Categorical Values
6th International Conference on Process Mining (Technical University of Denmark, 14. October 2024 - 18. October 2024)
In: Andrea Delgado, Tijs Slaats (ed.): Process Mining Workshops 2024
DOI: 10.1007/978-3-031-82225-4_17
BibTeX: Download - Roider J., Zanca D., Eskofier B.:
Efficient Training of Recurrent Neural Networks for Remaining Time Prediction in Predictive Process Monitoring
BPM: International Conference on Business Process Management (Krakow, 1. September 2024 - 6. September 2024)
In: Andrea Marrella, Manuel Resinas, Mieke Jans, Michael Rosemann (ed.): Business Process Management, 22nd International Conference, BPM 2024, Krakow, Poland, September 1–6, 2024, Proceedings, Cham: 2024
DOI: 10.1007/978-3-031-70396-6
URL: https://link.springer.com/book/10.1007/978-3-031-70396-6
BibTeX: Download - Schlieper P., Luft H., Klede K., Strohmeyer C., Eskofier B., Zanca D.:
Enhancing unsupervised outlier model selection: A study on ireos algorithms
In: ACM Transactions on Knowledge Discovery from Data 18 (2024), Article No.: 178
ISSN: 1556-4681
DOI: 10.1145/3653719
BibTeX: Download - Schrupp B., Klede K., Raab R., Eskofier B.:
Simulation and Detection of Healthcare Fraud in German Inpatient Claims Data
International Conference on Computational Science 2024
In: Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (ed.): Computational Science -- ICCS 2024, Cham: 2024
DOI: 10.1007/978-3-031-63772-8_22
BibTeX: Download - Zürl M., Stoll P., Brehm I., Sueskind J., Raab R., Petermann J., Zanca D., Simon R., von Fersen L., Eskofier B.:
Automated long-term monitoring of stereotypical movement in polar bears under human care using machine learning
In: Ecological Informatics (2024), p. 102840
ISSN: 1574-9541
DOI: 10.1016/j.ecoinf.2024.102840
BibTeX: Download
2023
- Abdullahi I., Raab R., Küderle A., Eskofier B.:
Aligning Federated Learning with Existing Trust Structures in Health Care Systems
In: International Journal of Environmental Research and Public Health 20 (2023), Article No.: 5378
ISSN: 1661-7827
DOI: 10.3390/ijerph20075378
URL: https://www.mdpi.com/1660-4601/20/7/5378
BibTeX: Download - Altstidl TR., Nguyen A., Schwinn L., Köferl F., Mutschler C., Eskofier B., Zanca D.:
Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks
2023 International Joint Conference on Neural Networks (IJCNN) (Gold Coast, Australia, 18. June 2023 - 23. June 2023)
In: Proc. Intl. Joint Conf. Neural Netw. (IJCNN) 2023
DOI: 10.1109/IJCNN54540.2023.10191724
BibTeX: Download - Dumbach P., Schwinn L., Löhr T., Do PL., Eskofier B.:
Artificial intelligence trend analysis on healthcare podcasts using topic modeling and sentiment analysis: a data-driven approach
In: Evolutionary Intelligence (2023)
ISSN: 1864-5909
DOI: 10.1007/s12065-023-00878-4
URL: https://link.springer.com/article/10.1007/s12065-023-00878-4
BibTeX: Download - Dumbach P., Schwinn L., Löhr T., Elsberger T., Eskofier B.:
Artificial intelligence trend analysis in German business and politics: a web mining approach
In: International Journal of Data Science and Analytics (2023), p. 1-22
ISSN: 2364-415X
DOI: 10.1007/s41060-023-00483-9
URL: https://link.springer.com/article/10.1007/s41060-023-00483-9
BibTeX: Download - Gabler E., Nissen M., Altstidl TR., Titzmann A., Packhäuser K., Maier A., Fasching P., Eskofier B., Leutheuser H.:
Fetal Re-Identification in Multiple Pregnancy Ultrasound Images Using Deep Learning
45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 (Sydney, NSW, 24. July 2023 - 27. July 2023)
In: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) 2023
DOI: 10.1109/EMBC40787.2023.10340336
BibTeX: Download - Klede K., Altstidl TR., Zanca D., Eskofier B.:
p-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison
Thirty-seventh Annual Conference on Neural Information Processing Systems (New Orleans, 10. December 2023 - 16. December 2023)
In: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine (ed.): Advances in Neural Information Processing Systems 36 2023
Open Access: https://proceedings.neurips.cc/paper_files/paper/2023/file/563d94819f68cb73d6a382809e587b54-Paper-Conference.pdf
URL: https://proceedings.neurips.cc/paper_files/paper/2023/file/563d94819f68cb73d6a382809e587b54-Paper-Conference.pdf
BibTeX: Download - Klede K., Schwinn L., Zanca D., Eskofier B.:
FastAMI - A Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics
AAAI 2023 (Washington, D.C., 7. February 2023 - 14. February 2023)
In: Proceedings of the AAAI Conference on Artificial Intelligence, 37(7) 2023
DOI: 10.1609/aaai.v37i7.26003
URL: https://ojs.aaai.org/index.php/AAAI/article/view/26003
BibTeX: Download - Köferl F., Jami J., Li J., Zanca D., Eskofier B., Zürl M.:
Tracking the visitor: An optical indoor system for visitor research in museums
In: Sonja Thiel, Johannes C. Bernhardt (ed.): AI in Museums: Reflections, Perspectives and Applications, Transcript-Verlag, 2023, p. 287 - 294 (Edition Museum, Vol.74)
ISBN: 9783839467107
DOI: 10.14361/9783839467107
BibTeX: Download - Maier T., Kamm L., Heckmann A., Eskofier B.:
Homogeneous Soil Moisture Sensor with High Repeatability for Different Soil Depths
Sensor and Measurement Science International 2023 (Nuremberg, Germany, 8. May 2023 - 11. May 2023)
DOI: 10.5162/smsi2023/p32
BibTeX: Download - Raab R., Küderle A., Zakreuskaya A., Stern AD., Klucken J., Kaissis G., Rueckert D., Boll S., Eils R., Wagener H., Eskofier B.:
Federated electronic health records for the European Health Data Space
In: The Lancet Digital Health 5 (2023), p. e840-e847
ISSN: 2589-7500
DOI: 10.1016/S2589-7500(23)00156-5
URL: https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00156-5/fulltext
BibTeX: Download - Schwinn L., Raab R., Nguyen A., Zanca D., Eskofier B.:
Exploring misclassifications of robust neural networks to enhance adversarial attacks
In: Applied Intelligence (2023)
ISSN: 0924-669X
DOI: 10.1007/s10489-023-04532-5
BibTeX: Download - Zugarini A., Röthenbacher T., Klede K., Ernandes M., Eskofier B., Zanca D.:
Die Rätselrevolution: Automated German Crossword Solving
CLiC-it 2023 - Italian Conference on Computational Linguistics (Venice, 30. November 2023 - 2. December 2023)
In: Federico Boschetti, Gianluca E. Lebani, Bernardo Magnini, Nicole Novielli (ed.): Proceedings of the 9th Italian Conference on Computational Linguistics 2023
Open Access: https://ceur-ws.org/Vol-3596/paper54.pdf
URL: https://ceur-ws.org/Vol-3596/paper54.pdf
BibTeX: Download - Zürl M., Dirauf R., Köferl F., Steinlein N., Sueskind J., Zanca D., Brehm I., von Fersen L., Eskofier B.:
PolarBearVidID: A Video-Based Re-Identification Benchmark Dataset for Polar Bears
In: Animals 13 (2023), p. 801
ISSN: 2076-2615
DOI: 10.3390/ani13050801
BibTeX: Download
2022
- Hecht D., Pfahler T., Ullmann I., Altstidl TR., Amer N., Jin Y., Eskofier B., Vossiek M.:
In Vivo Skin-Type Classification Using Millimeter-Wave Near-Field Probe Spectroscopy
2022 52nd European Microwave Conference (Milan, 27. September 2022 - 29. September 2022)
In: Institute of Electrical and Electronics Engineers (IEEE) (ed.): 2022 52nd European Microwave Conference, Milan: 2022
DOI: 10.23919/EuMC54642.2022.9924376
BibTeX: Download - Schwinn L., Bungert L., Nguyen A., Raab R., Pulsmeyer F., Precup D., Eskofier B., Zanca D.:
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification
Proceedings of the 39th International Conference on Machine Learning (Baltimore, USA, 17. July 2022 - 23. July 2022)
In: PMLR (ed.): 162 2022
Open Access: https://proceedings.mlr.press/v162/schwinn22a.html
URL: https://proceedings.mlr.press/v162/schwinn22a.html
BibTeX: Download - Zürl M., Stoll P., Brehm I., Raab R., Zanca D., Kabri S., Happold J., Nille H., Prechtel K., Wünsch S., Krause M., Seegerer S., von Fersen L., Eskofier B.:
Automated Video-Based Analysis Framework for Behavior Monitoring of Individual Animals in Zoos Using Deep Learning—A Study on Polar Bears
In: Animals 12 (2022), p. 692
ISSN: 2076-2615
DOI: 10.3390/ani12060692
BibTeX: Download
2021
- Altstidl TR., Kram S., Herrmann O., Stahlke M., Feigl T., Mutschler C.:
Accuracy-Aware Compression of Channel Impulse Responses using Deep Learning
International Conference on Indoor Positioning and Indoor Navigation (IPIN2021) (Lloret de Mar, 29. November 2021 - 2. December 2021)
In: Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN 2021) 2021
DOI: 10.1109/IPIN51156.2021.9662545
BibTeX: Download - Bungert L., Raab R., Roith T., Schwinn L., Tenbrinck D.:
CLIP: Cheap Lipschitz Training of Neural Networks
International Conference on Scale Space and Variational Methods in Computer Vision
In: Abderrahim Elmoataz, Jalal Fadili, Yvain Quéau, Julien Rabin, Loïc Simon (ed.): SSVM 2021: Scale Space and Variational Methods in Computer Vision, Cham: 2021
DOI: 10.1007/978-3-030-75549-2_25
URL: https://arxiv.org/abs/2103.12531
BibTeX: Download - Dumbach P., Liu R., Jalowski M., Eskofier B.:
The Adoption Of Artificial Intelligence In SMEs - A Cross-National Comparison In German And Chinese Healthcare
20th International Conference on Perspectives in Business Informatics Research (BIR 2021) Workshops (ILOG 2021) (Vienna, Austria (fully-virtual conference), 22. September 2021 - 24. September 2021)
In: Forbig P., Hinkelmann K., Kirikova M., Lantow B., Møller C., Morichetta A., Plebani P., Re B., Sandkuhl K., Seigerroth U. (ed.): Joint Proceedings of the BIR 2021 Workshops and Doctoral Consortium co-located with 20th International Conference on Perspectives in Business Informatics Research (BIR 2021) 2021
URL: http://ceur-ws.org/Vol-2991/paper08.pdf
BibTeX: Download - Laut P., Dumbach P., Eskofier B.:
Integration of Artificial Intelligence in the Organizational Adoption – A Configurational Perspective
Forty-Second International Conference on Information Systems (Austin, 11. December 2021 - 15. November 2021)
In: Association for Information Systems (ed.): ICIS 2021 Proceedings 2021
URL: https://aisel.aisnet.org/icis2021/is_implement/is_implement/2/
BibTeX: Download - Schwinn L., Nguyen A., Raab R., Bungert L., Tenbrinck D., Zanca D., Burger M., Eskofier B.:
Identifying untrustworthy predictions in neural networks by geometric gradient analysis
Conference on Uncertainty in Artificial Intelligence (UAI) (Online, 27. July 2021 - 30. July 2021)
URL: https://arxiv.org/abs/2102.12196
BibTeX: Download - Schwinn L., Nguyen A., Raab R., Zanca D., Eskofier B., Tenbrinck D., Burger M.:
Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks
International Joint Conference on Neural Networks (IJCNN) (Online, 18. July 2021 - 22. July 2021)
DOI: 10.1109/ijcnn52387.2021.9534190
BibTeX: Download - Schwinn L., Raab R., Nguyen A., Zanca D., Eskofier B.:
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks
URL: https://arxiv.org/abs/2105.10304
BibTeX: Download
2020
- Dumbach P., Aly A., Zrenner M., Eskofier B.:
Exploration of Process Mining Opportunities In Educational Software Engineering - The GitLab Analyser
13th International Conference on Educational Data Mining (Ifrane, Morocco (Fully Virtual Conference), 10. July 2020 - 13. July 2020)
In: Anna N. Rafferty, Jacob Whitehill, Cristobal Romero, Violetta Cavalli-Sforza (ed.): Proceedings of the 13th International Conference on Educational Data Mining 2020
Open Access: https://educationaldatamining.org/files/conferences/EDM2020/papers/paper_239.pdf
URL: https://educationaldatamining.org/files/conferences/EDM2020/EDM2020Proceedings.pdf
BibTeX: Download - Groß T., Dirauf R., Freiling F.:
Systematic Analysis of Browser History Evidence
13th International Conference on Systematic Approaches to Digital Forensic Engineering (SADFE) (New York, 15. May 2020 - 15. May 2020)
In: IEEE (ed.): 2020 13th International Conference on Systematic Approaches to Digital Forensic Engineering (SADFE) 2020
DOI: 10.1109/SADFE51007.2020.00010
BibTeX: Download - Köferl F., Link J., Eskofier B.:
Application of SORT on Multi-Object Tracking and Segmentation
Conference on Computer Vision and Pattern Recognition; 5th BMTT MOTChallenge Workshop: Multi-Object Tracking and Segmentation (Seattle, WA, USA (Virtual), 19. June 2020 - 19. June 2020)
URL: https://motchallenge.net/workshops/bmtt2020/papers/Application_and_Adaptations_of_SORT_on_MOTS20.pdf
BibTeX: Download
(Working Paper) - Rüthlein M., Köferl F., Mehringer W., Eskofier B.:
Interactive Segmentation of RGB-D Indoor Scenes using Deep Learning
International Conference on Machine Learning; 2nd ICML 2020 Workshop on Human in the Loop Learning (Virtual Conference, 18. July 2020 - 18. July 2020)
BibTeX: Download
(Conference report)
2019
- Raab R., Driessens K.:
A generative policy gradient approach for learning to play text-based adventure games
BNAIC/BENELEARN 2019 (Brussels, 6. November 2019 - 8. November 2019)
In: Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019) 2019
Open Access: http://ceur-ws.org/Vol-2491/abstract18.pdf
BibTeX: Download
2017
- Maier T., Kamm L.:
Moisture Sensor for Gravitation Dependent Plant Watering
68th International Astronautical Conference (IAC) (Adelaide, Australia, 25. September 2017 - 29. September 2017)
URL: https://www.researchgate.net/publication/319939522_Moisture_sensor_for_gravitation_dependent_plant_watering
BibTeX: Download
2016
- Maier T., Kamm L.:
Capacitive Soil Moisture Sensor for Plant Watering
European Geosciences Union (EGU) 2016 General Assembly (Wien, Österreich, 17. April 2016 - 22. April 2016)
URL: https://meetingorganizer.copernicus.org/EGU2016/EGU2016-13805.pdf?pdf/https://meetingorganizer.copernicus.org/EGU2016/EGU2016-13805.pdf?pdf
BibTeX: Download
2015
- Selgrad K., Lier A., Köferl F., Stamminger M., Lohmann D.:
Lightweight, generative variant exploration for high-performance graphics applications
14th International Conference on Generative Programming: Concepts & Experiences (GPCE) (Pittsburgh, PA, 26. October 2015 - 27. October 2015)
In: ACM Bd. 51, Nr. 3 2015
DOI: 10.1145/2814204.2814220
BibTeX: Download