Search Results for author:
Found 2 papers, 1 papers with code
A Probabilistic Model to explain Self-Supervised Representation Learning
Self-supervised learning (SSL) learns representations by leveraging an auxiliary unsupervised task, such as classifying semantically related samples, e. g. different data augmentations or modalities.
Identifiability Results for Multimodal Contrastive Learning
Our work generalizes previous identifiability results by redefining the generative process in terms of distinct mechanisms with modality-specific latent variables.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
