Research in computer analysis of medical images bears many promises to improve patients'
health. However, a number of systematic challenges are slowing down the progress of the …

Validation metrics are key for tracking scientific progress and bridging the current chasm
between artificial intelligence research and its translation into practice. However, increasing …

Automatic program understanding and generation techniques could significantly advance
the productivity of programmers and have been widely studied by academia and industry …

Abstract Contrastive Language–Image Pre-training (CLIP) has shown remarkable success
in learning with cross-modal supervision from extensive amounts of image–text pairs …

Deep Neural Networks (DNNs) are being adopted as components in software systems.
Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the …

While the importance of automatic image analysis is continuously increasing, recent meta-
research revealed major flaws with respect to algorithm validation. Performance metrics are …

Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

Contrastive Language--Image Pre-training (CLIP) has shown remarkable success in
learning with cross-modal supervision from extensive amounts of image--text pairs collected …

Antimicrobial resistance has become a critical global health problem due to the abuse of
conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides …

The quest for determinism in machine learning has disproportionately focused on
characterizing the impact of noise introduced by algorithmic design choices. In this work, we …