Publications
The following publications provide an insight into the competences of the KISSKI consortium.
2026
Mit KISSKI-Mitteln finanzierte Publikationen
Ausgewählte Publikationen des KISSKI-Konsortiums (ohne KISSKI-Mittel finanziert)
2025
Mit KISSKI-Mitteln finanzierte Publikationen
Ephemeral Kubernetes: dynamically deleting and recreating clusters using Warewulf
Jonathan Decker, Julian Kunkel
2025 / J Supercomput 81, 1491
Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU
Jonathan Decker, Vincent Florens Hasse, Julian Kunkel
2025 / Algorithms 18, no. 6
Achieving Scalable AI Inference in a Unified Cloud and HPC Environment by Employing System of Systems Architecture Design
Jonathan Decker
2025 / PhD Thesis
Using EEG Frequency Attributions to Explain the Classifications of a Deep Neural Network for Sleep Staging
Paul Gräve, Tabea F. Steinbrinker, Franz Ehrlich, Philip Hempel, Philip Zaschke, Dagmar Krefting
2025 / <str>
Influence of Pacemaker Artifacts on Deep Neural Networks for ECG Classification
Lennart Graf, Philip Hempel, Tabea F.A. Steinbrinker, Stephan von Haehling, Dagmar Kreftig, Nicolai Spicher
2025 / Curr Dir Biomed Eng
Explainable AI associates ECG aging effects with increased cardiovascular risk in a longitudinal population study
Philip Hempel, Antonio H. Ribeiro, Marcus Vollmer, Theresa Bender, Marcus Dörr, Dagmar Kreftig, Nicolai Spicher"
2025 / Npj Digit Med
Biomechanical impact of cortical bone vs. traditional pedicle screw trajectories: a finite element study on lumbar spinal instrumentation
Xishan Li, Khaled H.A. Abdel-Latif, Jefrem Schwab, Xiang Zhou, Jie Yang, Zully M. Ritter, Arndt F. Schilling, Maximilian Reinhold
2025 / Front Bioeng Biotechnol.
Ethical AI: Towards Defining a Collective Evaluation Framework
Aasish Kumar Sharma, Dimitar Kyosev, Julian Kunkel
2025 / 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC)
Performance Analysis of Convolutional Neural Network By Applying Unconstrained Binary Quadratic Programming
Aasish Kumar Sharma, Sanjeeb Prashad Pandey, Julian Kunkel
2025 / 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC)
Explaining a Sex-Related Cardiovascular Risk Continuum
Tabea F.A. Steinbrinker, Philip Hempel, Dagmar Kreftig, Nicolai Spicher
2025 / Curr Dir Biomed Eng
A Secure Interactive and High Performance Processing Environment for Collaborative Machine Learning Tasks on Large Data
Philip Zaschke, Jendrik Richter, Dagmar Kreftig
2025 / 70 Jahrestag Dtsch Ges Für Med Inform Biom Epidemiol E V GMDS
Quantized Inverse Design for Photonic Integrated Circuits
Frederik Schubert, Yannik Mahlau, Konrad Bethmann, Fabian Hartmann, Reinhard Caspary, Marco Munderloh, Jörn Ostermann, Bodo Rosenhahn
2025 / ACS Omega
QPM: Discrete Optimization for Globally Interpretable Image Classification
Thomas Norrenbrock, Timo Kaiser, Sovan Biswas, Ramesh Manuvinakurike, Bodo Rosenhahn
2025 / The Thirteenth International Conference on Learning Representations (ICLR)
Explainable Reinforcement Learning via Dynamic Mixture Policies
Maximilian Schier, Frederik Schubert, Bodo Rosenhahn
2025 / 2025 IEEE International Conference on Robotics and Automation (ICRA)
Multi-Flow - Multi-View-Enriched Normalizing Flows for Industrial Anomaly Detection
Mathis Kruse, Bodo Rosenhahn
2025 / Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR) Workshops
CHiQPM - Calibrated Hierarchical Interpretable Image Classification
Thomas Norrenbrock, Timo Kaiser, Sovan Biswas, Neslihan Kose, Ramesh Manuvinakurike, Bodo Rosenhahn
2025 / The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS)
UncertainSAM - Fast and Efficient Uncertainty Quantification of the Segment Anything Model
Timo Kaiser, Thomas Norrenbrock, Bodo Rosenhahn
2025 / Forty-second International Conference on Machine Learning (ICML)
Integrating 68Ga-PSMA-11 PET/CT with Clinical Risk Factors for Enhanced Prostate Cancer Progression Prediction
Joanna M. Wybranska, Lorenz Pieper, Christian Wybranski, Philipp Genseke, Jan Wuestemann, Julian Varghese, Michael C. Kreissl, Jakub Mitura
2025 / Cancers 2025, 17(14), 2285
BioLinkerAI: Leveraging LLMs to Improve Biomedical Entity Linking and Knowledge Capture
Ahmad Sakor, Kuldeep Singh, Maria-Esther Vidal
2025 / WSDM '25: Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining
Ausgewählte Publikationen des KISSKI-Konsortiums (ohne KISSKI-Mittel finanziert)
Adapting 12-Lead ECG AI Model to 1-Lead Smart Watches for Diagnosis in Clinical Heart Failure Patients
Philip Hempel, Tabea Steinbrinker, Lennart Graf, Sören Sievers, Gabriel Riedemann, Till Machereich
2025 / 47th Annu Int Conf IEEE Eng Med Biol Soc EMBC
Predicting ECG Age in 24-hour Holter Recordings of Heart Failure Patients
Philip Hempel, Tabea F.A. Steinbrinker", L. Graf, H. Dathe, Nicolai Spicher, Dagmar Kreftig
2025 / Curr Dir Biomed Eng.
BenchXAI: Comprehensive benchmarking of post-hoc explainable AI methods on multi-modal biomedical data
Jacqueline Michelle Metsch, Anne-Christine Hauschild
2025 / <str>
Few-Shot Whole Slide Pathology Classification with Multi-Granular Vision-Language Models
Anh-Tien Nguyen, Duy Minh Ho Nguyen, Nghiem Tuong Diep, Trung Quoc Nguyen, Nhat Ho, Jacqueline Michelle Metsch, Miriam Cindy Maurer, Daniel Sonntag, Hanibal Bohnenberger, Anne-Christin Hauschild
2025 / CLR 2025 FM-Wild Workshop
Curriculum Learning using Real and Simulated Data in Deep Learning Models for Electrocardiography Classification
Sebastian Schmale, Philip Hempel, Nicolai Spicher
2025 / IEEE
Creating synthetic data for the presentation of a post-COVID algorithm
Tabea Tharra, Ulrich Sax, Jonas Hügel
2025 / 70 Jahrestag Dtsch Ges Für Med Inform Biom Epidemiol E V GMDS
A somnologist’s guide to explainable deep neural networks for sleep scoring
Philip Zaschke, Miriam Cindy Maurer, Philip Hempel, Anne-Christin Hauschild, Andrea Rodenbeck, Nicolai Spicher
2025 / Somnologie
YESciEval - Robust LLM-as-a-Judge for Scientific Question Answering
Jennifer D'Souza, Hamed Babaei Gigiou, Quantin Münch
2025
LLMs4SchemaDiscovery: A Human-in-the-Loop Workflow for Scientific Schema Mining with Large Language Models
Sameer Sadruddin, Jennifer D'Souza, Eleni Poupaki, Alex Watkins, Hamed Babaei Giglou, Anisa Rula, Bora Karasulu, Soeren Auer, Adrie Mackus, Erwin Kessels
2025 / Extended Semantic Web Conference (ESWC)
OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignment
Hamed Babaei Giglou, Jennifer D'Souza, Oliver Karras, and Sören Auer
2025 / Extended Semantic Web Conference (ESWC)
Evaluating Scientific Question Answering in the Era of Large Language Models toward a Trustworthy Question & Answer Application
Quentin Münch
2025 / Master Thesis
2024
Publications financed with KISSKI funds
Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
Yannik Mahlau, Frederik Schubert, Bodo; Rosenhahn
2024 / Proceedings of the 41st International Conference on Machine Learning (ICML)
Q-SENN: Quantized Self-Explaining Neural Networks
Thomas Norrenbrock, Marco Rudolph, Bodo Rosenhahn
2024 / AAAI Technical Track on Safe, Robust and Responsible AI
Robust Shape Fitting for 3D Scene Abstraction
Florian Kluger, Eric Brachmann, Michael Ying Yang, Bodo Rosenhahn
2024 / IEEE transactions on pattern analysis and machine intelligence (TPAMI)
SplatPose and Detect: Pose-Agnostic 3D Anomaly Detection
Mathis Kruse, Marco Rudolph, Dominik Woiwode, Bodo Rosenhahn
2024 / CVPW-WS, VAND Visual Anomaly and Novelty Detection
PARSAC: Accelerating Robust Multi-Model Fitting with Parallel Sample Consensus
Florian Kluger, Bodo Rosenhahn
2024 / AAAI
Estimation and aggregation of wind power forecasts utilizing master data and zero-shot learning
Dominik Beinert, Johannes M F Schütz, Axel Braun
2024 / 23rd Wind & Solar Integration Workshop
Selected publications of the KISSKI consoritum (financed without KISSKI funds)
Privacy Protection Behaviors from a New Angle: Exploratory Analysis on a Russian Sample
Denis Obrezkov
2024 / Proceedings on Privacy Enhancing Technologies Symposium
FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing
Cong,Yuren, Mengmeng Xu, Christian Simon, Shoufa Chen, Jiawei Ren, Yanping Xie, Juan-Manuel Perez-Rua, Bodo Rosenhahn, Xiang,Tao, Sen; He
2024 / International Conference on Learning Representations (ICLR)
2023
Publications financed with KISSKI funds
Compensation Learning in Semantic Segmentation
Timo Kaiser, Christoph Reinders, Bodo; Rosenhahn
2023 / Computer Vision and Pattern Recognition Workshops (CVPRW)
HyperSparse Neural Networks: Shifting Exploration to Exploitation through Adaptive Regularization
Patrick Glandorf*, Timo Kaiser*, Bodo Rosenhahn, (*contributed equally)
2023 / International Conference on Computer Vision Workshops (ICCVW)
Personalized 3D Human Pose and Shape Refinement
Tom Wehrbein, Bodo Rosenhahn, Iain Matthews, Carsten; Stoll
2023 / International Conference on Computer Vision Workshops (ICCVW)
Human Spine Motion Capture using Perforated Kinesiology Tape
Hendrik Hachmann, Bodo Rosenhahn
2023 / Computer Vision and Pattern Recognition Workshops (CVPRW)
AutoML in heavily constrained applications
Felix Neutatz, Marius Lindauer, Ziawasch Abedjan
2023 / VLDB Journal
The voraus-AD Dataset for Anomaly Detection in Robot Applications
Jan Thieß Brockmann*, Marco Rudolph*, Bodo Rosenhahn, Bastian Wandt, (* equal contribution)
2023 / Transactions on Robotics
Selected publications of the KISSKI consoritum (financed without KISSKI funds)
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection
Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, Bastian Wandt
2023
Learning Activation Functions for Sparse Neural Networks
Mohammed Loni, Aditya Mohan, Mehdi Asadi, Marius Lindauer
2023 / International Conference on Automated Machine Learning
Organizing Scholarly Knowledge in the Open Research Knowledge Graph An Open-Science Platform for FAIR Scholarly Knowledge
Sören Auer, Markus Stocker, Oliver Karras, Allard Oelen, Jennifer D'Souza, Anna-Lena Lorenz
2023
Increasing Reproducibility in Science by Interlinking Semantic Artifact Descriptions in a Knowledge Graph
Hassan Hussein, Kheir Eddine Farfar, Allard Oelen, Oliver Karras, Sören Auer
2023
KPI Extraction from Maintenance Work Orders — A Comparison of Expert Labeling, Text Classification and AI-Assisted Tagging for Computing Failure Rates of Wind Turbines
Marc-Alexander Lutz, Bastian Schäfermeier, Rachael Sexton, Michael Sharp, Alden Dima, Stefan Faulstich, Jagan Mohini Aluri
2023 / Energies
Optimization of Sparsity-Constrained Neural Networks as a Mixed Integer Linear Program
Bodo Rosenhahn
2023 / Journal of Optimization Theory and Applications
Multi-Resolution Segmentation of Solar Photovoltaic Systems Using Deep Learning
Maximilian Kleebauer, Christopher Marz, Christoph Reudenbach, Martin Braun
2023 / Remote Sensing
Towards FAIR Semantic Publishing of Research Dataset Metadata in the Open Research Knowledge Graph
Raia Abu Ahmad, Jennifer D'Souza, Matthäus Zloch, Wolfgang Otto, Georg Rehm, Allard Oelen, Stefan Dietze, Sören Auer
2023
Power flow forecasts at transmission grid nodes using Graph Neural Networks
Dominik Beinert, Clara Holzhüter, Josephine M. Thomas, Stephan Vogt
2023 / Energy and AI
RelTR: Relation Transformer for Scene Graph Generation
Yuren Cong, Michael Yang, Bodo; Rosenhahn
2023 / IEEE transactions on pattern analysis and machine intelligence (TPAMI)
Deep Reinforcement Learning for Autonomous Driving Using High-Level Heterogeneous Graph Representations
Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
2023 / 2023 IEEE International Conference on Robotics and Automation (ICRA)
Secure HPC: A workflow providing a secure partition on an HPC system
Hendrik Nolte, Nicolai Spicher, Andrew Russel, Tim Ehlers, Sebastian Krey, Dagmar Krefting, Julian Kunkel
2023 / Future Generation Computer Systems
Targeted adversarial attacks on wind power forecasts
René Heinrich, Christoph Scholz, Stephan Vogt, Malte Lehna
2023 / Machine Learning
Exploiting Subword Permutations to Maximize CNN Compute Performance and Efficiency
Michael Beyer, Sven Gesper, Andre Guntoro, Guillermo Payá-Vayá, Holger Blume
2023 / International Conference on Application-specific Systems, Architectures and Processors (ASAP)
Contextualize Me - The Case for Context in Reinforcement Learning
Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, Sebastian Döhler, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer
2023 / Transactions on Machine Learning Research
Governance-Centric Paradigm: Overcoming the Information Gap between Users and Systems by Enforcing Data Management Plans on HPC-Systems
Hendrik Nolte, Julian Kunkel
2023 / INFOCOMP
Improving the Interpretability of ECoG-Signals by Identifying Significant Signal-Segments with Explainable AI
Julian Drewljau, Mesbah Alam, Joachim Krauss, Kerstin Schwabe, Holger Blume
2023 / Abstracts of the 57th Annual Meeting of the German Society of Biomedical Engineering
N2V2PRO: Neural Network Mapping Framework for a Custom Vector Processor Architecture
Sven Gesper, Gia Bao Thieu, Daniel Köhler, Markus Kock, Tim Berthold, Oliver Renke, Holger Blume, Guillermo Payá-Vayá
2023 / International Conference on Consumer Electronics-Berlin (ICCE-Berlin)
ZuSE Ki-Avf: Application-Specific AI Processor for Intelligent Sensor Signal Processing in Autonomous Driving
Thieu, Gia Bao, et al.
2023 / Design, Automation & Test in Europe Conference & Exhibition (DATE)
2022
Selected publications of the KISSKI consoritum (financed without KISSKI funds)
AI agents envisioning the future: Forecast-based operation of renewable energy storage systems using hydrogen with Deep Reinforcement Learning
Alexander Dreher, Thomas Bexten, Tobias Sieker, Malte Lehna, Jonathan Schütt, Christoph Scholz, Manfred Wirsum
2022 / Energy Conversion and Management
Efficient Automated Deep Learning for Time Series Forecasting
Difan Deng, Florian Karl, Frank Hutter, Bernd Bischl, Marius Lindauer
2022 / European Conference on Machine Learning (ECML)
Constrained Mean Shift Clustering
Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
2022 / Proceedings of the 2022 SIAM International Conference on Data Mining (SDM)
ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing
Christoph Reinders, Frederik Schubert, Bodo Rosenhahn
2022 / 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI)
Hands-free AutoML via Meta-Learning
Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
2022 / Journal of Machine Learning Research
LMGP: Lifted Multicut Meets Geometry Projections for Multi-Camera Multi-Object Tracking
Duy Nguyen, Roberto Henschel, Bodo Rosenhahn, Daniel Sonntag, Paul Swoboda
2022 / Computer Vision and Pattern Recognition (CVPR)
A Reinforcement Learning approach for the continuous electricity market of Germany: Trading from the perspective of a wind park operator
Malte Lehna, Björn Hoppmann, Christoph Scholz, René Heinrich
2022 / Energy and AI
Secure Authorization for RESTful HPC Access with FaaS Support
Christian Köhler, Mohammed Hossein Biniaz, Sven Bingert, Hendrik Nolte, Julian Kunkel
2022 / International Journal on Advances in Security
Performance Evaluation of Open-Source Serverless Platforms for Kubernetes
Jonathan Decker, Piotr Kasprzak, Julian Martin Kunkel
2022 / Algorithms
Take 5: Interpretable Image Classification with a Handful of Features
Thomas Norrenbrock, Marco Rudolph, Bodo; Rosenhahn
2022 / Progress and Challenges in Building Trustworthy Embodied AI @NeurIPS
Predictive accuracy of CNN for cortical oscillatory activity in an acute rat model of parkinsonism
Ali Abdul Nabi Ali, Mesbah Alam, Simon Klein, Nicolai Behmann, Joachim K. Krauss, Theodor Doll, Holger Blume, Kerstin Schwabe
2022 / Neural Networks
2021
Selected publications of the KISSKI consoritum (prior to KISSKI project start)
Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL
Lucas Zimmer, Marius Lindauer, Frank Hutter
2021 / IEEE Transactions on Pattern Analysis and Machine Intelligence
Autoencoder-based anomaly root cause analysis for wind turbines
Cyriana M.A. Roelofs, Marc-Alexander Lutz, Stefan Faulstich, Stephan Vogt
2021 / Energy and AI
Compact representations for efficient storage of semantic sensor data
Farah Karim, Maria-Esther Vidal, Sören Auer
2021
Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows
Tom Wehrbein, Marco Rudolph, Bodo Rosenhahn, Bastian Wandt
2021 / International Conference on Computer Vision (ICCV)
Semi-automatic generation of training samples for detecting renewable energy plants in high-resolution aerial images
Maximilian Kleebauer, Daniel Horst, Christopher Reudenbach
2021 / Remote Sensing
Fixed Point Analysis Workflow for efficient Design of Convolutional Neural Networks in Hearing Aids
Simon Klein, Jonas Kantic, Holger Blume
2021 / Current Directions in Biomedical Engineering