ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...

Abstract: Recent works try to combine clustering and contrastive learning for unsupervised out-of-distribution (OOD) detection, since these two schemes can exploit semantic information and bring in ...

Morphological profiling has recently demonstrated remarkable potential for identifying the biological activities of small molecules. Alongside the fully supervised and self-supervised machine learning ...

Abstract: Previous contrastive learning methods for sentence representations often focus on insensitive transformations to produce positive pairs, but neglect the role of sensitive transformations ...