Search Results for author:
Found 2 papers, 1 papers with code
Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images
We propose a Deep Variational Clustering (DVC) framework for unsupervised representation learning and clustering of large-scale medical images.
Deep Bregman Divergence for Contrastive Learning of Visual Representations
In this paper, we propose deep Bregman divergences for contrastive learning of visual representation where we aim to enhance contrastive loss used in self-supervised learning by training additional networks based on functional Bregman divergence.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
