Abstract: Contrastive learning (CL) has emerged as a powerful approach for self-supervised learning. However, it suffers from sampling bias, which hinders its performance. While the mainstream ...

Thomas Helbling is an Advisor in the IMF’s Research Department. Opinions expressed in articles and other materials are those of the authors; they do not necessarily reflect IMF policy.

Abstract: Negative sampling is an essential part in knowledge graph embedding, which offers significant advantages to numerous downstream related tasks. There are two kinds of important negatives: ...

This Conceptual Analysis traces who pays for environmental footprints, focusing on the current US economic system and environmental regulatory regime. With some important exceptions, carbon, water, ...

Large, unrestricted philanthropic gifts can be transformative for nonprofit organizations. The research increasingly shows that many recipients use these gifts carefully: building reserves, ...