2 citations · 2 across the 3 of their papers we have counts for
3 papers
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…
ADAPT: Multimodal Learning for Detecting Physiological Changes under Missing Modalities
Julie Mordacq, Leo Milecki, Maria Vakalopoulou +2
Multimodality has recently gained attention in the medical domain, where imaging or video modalities may be integrated with biomedical signals or health records. Yet, two challenge…