181 citations
- Technical University of MunichDE13 papers
- Ludwig-Maximilians-Universität MünchenDE8 papers
- University of ZurichCH3 papers
- Accadis Hochschule Bad HomburgDE2 papers
- Czech Technical University in PragueCZ2 papers
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE2 papers
- Fraunhofer Institute for Integrated Systems and Device TechnologyDE2 papers
- Infineon Technologies (Germany)DE2 papers
- University of AmsterdamNL2 papers
- Aix-Marseille UniversitéFR1 paper
- Alice Films (France)FR1 paper
- Alpine Quantum Technologies (Austria)AT1 paper
32 papers
CUBICS: Situation-aware performance estimation for safety-relevant ML components
Benjamin Herd, Jessica Kelly, Mario Trapp
Machine learning (ML) is a key technology driving innovation today, but ensuring ML safety remains a major challenge for safety-related applications. A promising idea is to build p…
Optimizing Experimental Design for Causal Effect Estimation with Partial Measurements
Leopold Mareis
Instrumental variable regression quantifies causal effects between a possibly confounded treatment variable and a response variable by leveraging an instrument $ X_…
A Subjective Logic-based method for runtime confidence updates in safety arguments
Benjamin Herd, Jessica Kelly, Clarissa Heinemann +1
We present a method for dynamic quantitative assurance that enhances static safety cases with continuous, runtime-driven confidence updates. The method quantifies and propagates co…
Skin-Machine Interface with Multimodal Contact Motion Classifier
Alberto Confente, Takanori Jin, Taisuke Kobayashi +2
This paper proposes a novel framework for utilizing skin sensors as a new operation interface of complex robots. The skin sensors employed in this study possess the capability to q…
Towards Open-World Human Action Segmentation Using Graph Convolutional Networks
Hao Xing, Kai Zhe Boey, Gordon Cheng
Human-object interaction segmentation is a fundamental task of daily activity understanding, which plays a crucial role in applications such as assistive robotics, healthcare, and…
Generalization Bounds in Hybrid Quantum-Classical Machine Learning Models
Tongyan Wu, Amine Bentellis, Alona Sakhnenko +1
Hybrid classical-quantum models aim to harness the strengths of both quantum computing and classical machine learning, but their practical potential remains poorly understood. In t…