Publications

We present a novel approach to learning visual representations through self-supervised training. Our method demonstrates significant improvements over existing approaches, particularly in scenarios with limited labeled data.

We present a theoretical framework for understanding multi-modal learning systems. Our analysis reveals key insights into the interaction between different modalities.