T-REGS: Minimum Spanning Tree Regularization for Self-Supervised Learning
NeurIPSSpotlight2025
TL;DR
Self-supervised learning (SSL) has emerged as a powerful paradigm for learning representations without labeled data, often by enforcing invariance to input transformations such as rotations or blurrin…
Opening excerpt from the authors’ abstract. source
Read the paper
Topics
self-supervised
← All NeurIPS 2025 Spotlight papers · Browse the whole archive