Representation Learning
Applications such as disaster management enormously benefit from rapid availability of satellite observations.
Traditionally, data …
This work introduces a novel principle we call disentanglement via mechanism sparsity regularization, which can be applied when the …
Contrastive self-supervised learning has emerged as a promising approach to unsupervised visual representation learning. In general, …