Spatial duration-augmented SPEI modeling over Italy reveals a strong south–north drought-memory gradient and shows BATs distributions dominate standard SPEI candidates while RET choice barely moves the signal.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
roles
background 1polarities
background 1representative citing papers
LeJEPA derives an optimal isotropic Gaussian target for embeddings and enforces it via sketched regularization to deliver scalable, heuristics-free self-supervised pretraining with 79% ImageNet linear accuracy on ViT-H/14.
citing papers explorer
-
A spatial duration-augmented framework for drought persistence
Spatial duration-augmented SPEI modeling over Italy reveals a strong south–north drought-memory gradient and shows BATs distributions dominate standard SPEI candidates while RET choice barely moves the signal.
-
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
LeJEPA derives an optimal isotropic Gaussian target for embeddings and enforces it via sketched regularization to deliver scalable, heuristics-free self-supervised pretraining with 79% ImageNet linear accuracy on ViT-H/14.