2 citations · 2 across the 3 of their papers we have counts for
3 papers · 1 filter
IdEst: Assessing Self-Supervised Learning Representations via Intrinsic Dimension
Julie Mordacq, Vicky Kalogeiton, Steve Oudot
Self-supervised learning (SSL) has emerged as a powerful paradigm for learning meaningful representations from unlabeled data. However, the standard protocol for evaluating these r…
T-REGS: Minimum Spanning Tree Regularization for Self-Supervised Learning
Julie Mordacq, David Loiseaux, Vicky Kalogeiton +1
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…
D-GRIL: End-to-End Topological Learning with 2-parameter Persistence
Soham Mukherjee, Shreyas N. Samaga, Cheng Xin +2
End-to-end topological learning using 1-parameter persistence is well-known. We show that the framework can be enhanced using 2-parameter persistence by adopting a recently introdu…