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08/03/2023
Assessing Systematic Weaknesses of DNNs using Counterfactuals
With the advancement of DNNs into safety-critical applications, testing ...
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06/20/2023
Guideline for Trustworthy Artificial Intelligence – AI Assessment Catalog
Artificial Intelligence (AI) has made impressive progress in recent year...
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05/02/2022
A Survey on Uncertainty Toolkits for Deep Learning
The success of deep learning (DL) fostered the creation of unifying fram...
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04/29/2022
Tailored Uncertainty Estimation for Deep Learning Systems
Uncertainty estimation bears the potential to make deep learning (DL) sy...
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06/10/2021
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis
Many machine learning applications can benefit from simulated data for s...
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04/22/2021
Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities
An important pillar for safe machine learning (ML) is the systematic mit...
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04/19/2021
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation
Data-driven sensor interpretation in autonomous driving can lead to high...
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01/07/2021
A Novel Regression Loss for Non-Parametric Uncertainty Optimization
Quantification of uncertainty is one of the most promising approaches to...
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12/23/2020
Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties
Quantification of uncertainty is one of the most promising approaches to...
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12/17/2020
DenseHMM: Learning Hidden Markov Models by Learning Dense Representations
We propose DenseHMM - a modification of Hidden Markov Models (HMMs) that...
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07/10/2020