Fermi-Bose Machine: A Local Contrastive Learning Approach for Semantically Meaningful and Adversarially Robust Representations

The Fermi-Bose Machine (FBM) proposes a local contrastive learning approach to learn semantically meaningful and adversarially robust representations by geometrically separating the internal representations of neural networks.