Publikationen 2023 - Fraunhofer IKS

Jahr Year	Titel/Autor:in Title/Author	Publikationstyp Publication Type
2023	(Some) efforts towards application driven benchmarks in Germany Lorenz, Jeanette Miriam	Vortrag Presentation
2023	Adaptively Managing Reliability of Machine Learning Perception under Changing Operating Conditions Salvi, Aniket; Weiß, Gereon; Trapp, Mario	Konferenzbeitrag Conference Paper
2023	Addressing uncertainty in the safety assurance of machine-learning Burton, Simon; Herd, Benjamin	Zeitschriftenaufsatz Journal Article
2023	AI for Safety: How to use Explainable Machine Learning Approaches for Safety Analyses Kurzidem, Iwo; Burton, Simon; Schleiß, Philipp	Konferenzbeitrag Conference Paper
2023	Are Transformers More Robust? Towards Exact Robustness Verification for Transformers Liao, Brian Hsuan-Cheng; Cheng, Chih-Hong; Esen, Hasan; Knoll, Alois	Konferenzbeitrag Conference Paper
2023	Assessable and interpretable sensitivity analysis in the pattern graph framework for nonignorable missingness mechanisms Zamanian, Alireza; Ahmidi, Narges; Drton, Mathias	Zeitschriftenaufsatz Journal Article
2023	Automated characterization and detection of fibromyalgia using slow wave sleep EEG signals with glucose pattern and D’hondt pooling technique Karabey Aksalli, Isil; Baygin, Nursena; Hagiwara, Yuki; Paul, Jose Kunnel; Iype, Thomas; Koh, Joel E. W.; Barua, Prabal Datta; Baygin, Mehmet; Dogan, Sengul; Tuncer, Turker; Acharya, U. Rajendra	Zeitschriftenaufsatz Journal Article
2023	Butterfly Effect Attack: Tiny and Seemingly Unrelated Perturbations for Object Detection Doan, Nguyen Anh Vu; Yüksel, Arda; Cheng, Chih-Hong	Konferenzbeitrag Conference Paper
2023	Can Conformal Prediction Obtain Meaningful Safety Guarantees for ML Models? Seferis, Emmanouil; Burton, Simon; Cheng, Chih-Hong	Vortrag Presentation
2023	Closing the gaps: Complexity and uncertainty in the safety assurance and regulation of automated driving Burton, Simon; McDermid, John Alexander	Paper
2023	Complexity, uncertainty and the Safety of ML Burton, Simon; Herd, Benjamin	Paper
2023	Concept Correlation and its Effects on Concept-Based Models Heidemann, Lena; Monnet, Maureen; Roscher, Karsten	Konferenzbeitrag Conference Paper
2023	DevOps in Robotics: Challenges and Practices Sawczuk da Silva, Alexandre; Kreutz, Andreas; Weiß, Gereon; Rothe, Johannes; Ihrke, Christoph	Konferenzbeitrag Conference Paper
2023	Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Franco, Nicola; Korth, Daniel; Lorenz, Jeanette Miriam; Roscher, Karsten; Günnemann, Stephan	Konferenzbeitrag Conference Paper
2023	Guest Editorial Special Issue on Sensing and Machine Learning for Automotive Perception Santra, Avik; Pandharipande, Ashish; Wang, Pu Perry; Gurbuz, Sevgi Zubeyde; Ibañez-Guzmãn, Javier; Cheng, Chih-Hong; Dauwels, Justin; Li, Guofa	Editorial
2023	Optimizing hyperparameters using the geometric difference Egginger, Sebastian; Sakhnenko, Alona; Runge, Xiomara; Lorenz, Jeanette Miriam	Poster
2023	Out-of-Distribution Detection for Reinforcement Learning Agents with Probabilistic Dynamics Models Haider, Tom; Roscher, Karsten; Schmoeller da Roza, Felippe; Günnemann, Stephan	Konferenzbeitrag Conference Paper
2023	Post-hoc Saliency Methods Fail to Capture Latent Feature Importance in Time Series Data Schröder, Maresa; Zamanian, Alireza; Ahmidi, Narges	Konferenzbeitrag Conference Paper
2023	Potential-based Credit Assignment for Cooperative RL-based Testing of Autonomous Vehicles Ayvaz, Utku; Cheng, Chih-Hong; Hao, Shen	Konferenzbeitrag Conference Paper
2023	Preventing Errors in Person Detection: A Part-Based Self-Monitoring Framework Schwaiger, Franziska; Matic-Flierl, Andrea; Roscher, Karsten; Günnemann, Stephan	Konferenzbeitrag Conference Paper
2023	Proteomics reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients Bauer, Alina; Pachl, Elisabeth; Hellmuth, Johannes C.; Kneidinger, Nikolaus; Motaharehsadat, Heydarian; Frankenberger, Marion; Stubbe, Hans C.; Ryffel, Bernhard; Petrera, Agnese; Hauck, Stefanie M.; Behr, Jürgen; Kaiser, Rainer; Scherer, Clemens; Deng, Li; Teupser, Daniel; Ahmidi, Narges; Muenchhoff, Maximilian; Schubert, Benjamin; Hilgendorff, Anne	Zeitschriftenaufsatz Journal Article
2023	Quantum computing in assistance to solve combinatorial optimization problems Lorenz, Jeanette Miriam	Vortrag Presentation
2023	Quantum Reinforcement Learning for Aerospace Tandon, Akshat; Dragan, Theodora-Augustina	Vortrag Presentation
2023	Quantum Reinforcement Learning for Solving a Stochastic Frozen Lake Environment and the Impact of Architecture and Optimizer Choices Dragan, Theodora-Augustina; Monnet, Maureen; Mendl, Christian B.; Lorenz, Jeanette Miriam	Vortrag Presentation
2023	Quantum Reinforcement Learning for Solving a Stochastic Frozen Lake Environment and the Impact of Quantum Architecture Choices Dragan, Theodora-Augustina; Monnet, Maureen; Mendl, Christian B.; Lorenz, Jeanette Miriam	Konferenzbeitrag Conference Paper
2023	Quantum-enhanced AI in medicine Lorenz, Jeanette Miriam	Vortrag Presentation
2023	QuaST - Quantum enabling Services and Tools for industrial applications Lorenz, Jeanette Miriam	Vortrag Presentation
2023	Randomized Smoothing (almost) in Real Time? Seferis, Emmanouil; Kollias, Stefanos; Burton, Simon	Poster
2023	Recommending Solution Paths for Solving Optimization Problems with Quantum Computing Poggel, Benedikt; Quetschlich, Nils; Burgholzer, Lukas; Wille, Robert; Lorenz, Jeanette Miriam	Konferenzbeitrag Conference Paper
2023	Safe and Efficient Operation with Constrained Hierarchical Reinforcement Learning Schmoeller da Roza, Felippe; Roscher, Karsten; Günnemann, Stephan	Konferenzbeitrag Conference Paper
2023	Safe, Ethical and Sustainable: Framing the Argument McDermid, John Alexander; Porter, Zoe; Burton, Simon	Konferenzbeitrag Conference Paper
2023	Safety Assurance with Ensemble-based Uncertainty Estimation and overlapping alternative Predictions in Reinforcement Learning Eilers, Dirk; Burton, Simon; Schmoeller da Roza, Felippe; Roscher, Karsten	Konferenzbeitrag Conference Paper
2023	Sensing and Machine Learning for Automotive Perception: A Review Pandharipande, Ashish; Cheng, Chih-Hong; Dauwels, Justin; Gurbuz, Sevgi Z.; Ibanez-Guzman, Javier; Li, Guofa; Piazzoni, Andrea; Wang, Pu; Santra, Avik	Zeitschriftenaufsatz Journal Article
2023	Statistical Property Testing for Generative Models Seferis, Emmanouil; Burton, Simon; Cheng, Chih-Hong	Vortrag Presentation
2023	The Effect of Data Encoding on Quantum Convolutional Neural Networks Chaabani, Nermine; Dragan, Theodora-Augustina; Lorenz, Jeanette Miriam	Vortrag Presentation
2023	Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models Sinhamahapatra, Poulami; Heidemann, Lena; Monnet, Maureen; Roscher, Karsten	Vortrag Presentation
2023	Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models Sinhamahapatra, Poulami; Heidemann, Lena; Monnet, Maureen; Roscher, Karsten	Konferenzbeitrag Conference Paper
2023	Towards Probabilistic Safety Guarantees for Model-Free Reinforcement Learning Schmoeller da Roza, Felippe; Roscher, Karsten; Günneman, Stephan	Paper
2023	Towards Safety Assurance of Uncertainty-Aware Reinforcement Learning Agents Schmoeller da Roza, Felippe; Hadwiger, Simon; Thorn, Ingo; Roscher, Karsten	Konferenzbeitrag Conference Paper
2023	Towards Uncertainty Reduction Tactics for Behavior Adaptation Kreutz, Andreas; Weiß, Gereon; Trapp, Mario	Konferenzbeitrag Conference Paper
2023	Uncertainty-Aware Hierarchical Reinforcement Learning Robust to Noisy Observations Schmoeller da Roza, Felippe	Konferenzbeitrag Conference Paper
2023	What about the Latent Space? The Need for Latent Feature Saliency Detection in Deep Time Series Classification Schröder, Maresa; Zamanian, Alireza; Ahmidi, Narges	Zeitschriftenaufsatz Journal Article

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