Forschungsarbeiten des KISSKI Konsortiums


Die folgenden Publikationen geben einen Einblick in die Kompetenzen des KISSKI Konsortiums.


Mit KISSKI-Mitteln finanzierte Publikationen

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

Ausgewählte Publikationen des KISSKI-Konsortiums (ohne KISSKI-Mittel finanziert)

Asymmetric Student-Teacher Networks for Industrial Anomaly Detection

Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, Bastian Wandt


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


Increasing Reproducibility in Science by Interlinking Semantic Artifact Descriptions in a Knowledge Graph

Hassan Hussein, Kheir Eddine Farfar, Allard Oelen, Oliver Karras, Sören Auer


Optimization of Sparsity-Constrained Neural Networks as a Mixed Integer Linear Program

Bodo Rosenhahn

2023 / Journal of Optimization Theory and Applications

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


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)

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


Ausgewählte Publikationen des KISSKI-Konsortiums (ohne KISSKI-Mittel finanziert)

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)

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


Ausgewählte Publikationen des KISSKI-Konsortiums (vor KISSKI-Projektbeginn)

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

Compact representations for efficient storage of semantic sensor data

Farah Karim, Maria-Esther Vidal, Sören Auer


Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows

Tom Wehrbein, Marco Rudolph, Bodo Rosenhahn, Bastian Wandt

2021 / International Conference on Computer Vision (ICCV)