In recent decades, wildfires have caused tremendous property losses, fatalities, and
extensive damage to forest ecosystems. Inspired by the abundance of publicly available …

Self-supervised learning (SSL) is a potential deep learning (DL) technique that uses
massive volumes of unlabeled data to train neural networks. SSL techniques have evolved …

Abstract Machine learning for differential equations paves the way for computationally
efficient alternatives to numerical solvers, with potentially broad impacts in science and …

Self-supervised learning (SSL) is a powerful technique for learning from unlabeled data. By
learning to remain invariant to applied data augmentations, methods such as SimCLR and …

Graph contrastive learning (GCL), learning the node representation by contrasting two
augmented graphs in a self-supervised way, has attracted considerable attention. GCL is …

Medical imaging technologies are generating increasingly large amounts of high-quality,
information-dense data. Despite the progress, practical use of advanced imaging …

Data analysis techniques can be powerful tools for rapidly analyzing data and extracting
information that can be used in a latent space for categorizing observations between classes …

Self-supervised learning, dubbed “the dark matter of intelligence” 1, is a promising path to
advance machine learning. As opposed to supervised learning, which is limited by the …