Yotam Norman

Unsupervised Representation Learning - an Invariant Risk Minimization Perspective

We propose a novel unsupervised framework for Invariant Risk Minimization (IRM), extending the concept of invariance to settings where labels are unavailable. Traditional IRM methods rely on labeled data to learn representations that are robust to distributional shifts across environments. In contra…