T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data

Bibliografske podrobnosti

izdano v:	arXiv.org (Dec 19, 2024), p. n/a
Glavni avtor:	Thimonier, Hugo
Drugi avtorji:	José Lucas De Melo Costa, Popineau, Fabrice, Rimmel, Arpad, Doan, Bich-Liên
Izdano:	Cornell University Library, arXiv.org
Teme:	Structured data Regularization methods Regularization Data augmentation Self-supervised learning Tables (data) Machine learning Decision trees Representations
Online dostop:	Citation/Abstract Full text outside of ProQuest
Oznake:	Označite Brez oznak, prvi označite!