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Guideline for Trustworthy Artificial Intelligence -- AI Assessment Catalog
Artificial Intelligence (AI) has made impressive progress in recent years and represents a key technology that has a crucial impact on the economy and society.
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis
We propose a novel framework consisting of a generative label-to-image synthesis model together with different transferability measures to inspect to what extent we can transfer testing results of semantic segmentation models from synthetic data to equivalent real-life data.
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Our paper addresses both machine learning experts and safety engineers: The former ones might profit from the broad range of machine learning topics covered and discussions on limitations of recent methods.
Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities
To address this constraint, we present an approach to detect learned shortcuts using an interpretable-by-design network as a proxy to the black-box model of interest.
Information-Theoretic Perspective of Federated Learning
An approach to distributed machine learning is to train models on local datasets and aggregate these models into a single, stronger model.
