Forschungsarbeiten des KISSKI Konsortiums

Publikationen

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

2024


Mit KISSKI-Mitteln finanzierte Publikationen

PARSAC: Accelerating Robust Multi-Model Fitting with Parallel Sample Consensus

Florian Kluger, Bodo Rosenhahn

2024 / AAAI

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

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


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

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

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

2023

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)

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

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


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)

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


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

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)

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