Although digital simulations are becoming increasingly important in the industrial world
owing to the transition toward Industry 4.0, as well as the development of digital twin …

Graph-level classification is a critical problem in social analysis and bioinformatics. Since
annotated labels are typically costly, we intend to study this challenging task in semi …

This work explores the effect of noisy sample selection in active learning strategies. We
show on both synthetic problems and real-life use-cases that knowledge of the sample noise …

Despite the vast body of literature on Active Learning (AL), there is no comprehensive and
open benchmark allowing for efficient and simple comparison of proposed samplers …

In Active learning, a trained model is used to select samples to label to maximize its
performance. Choosing the best sample selection strategy for a one-shot experiment is hard …

This work explores the effect of noisy sample selection in active learning strategies. We
show on both synthetic problems and reallife use-cases that knowledge of the sample noise …