You Don't Need Strong Assumptions: Visual Representation Learning via Temporal Differences

Research on Contrastive Representations for Temporal Reasoning in AI Systems

The article presents research on Contrastive Representations for Temporal Reasoning (CRTR), examining whether temporal reasoning can emerge

FlashAttention-T: Towards Tensorized Attention

Using Diffusion Models to Visualize What Self-Supervised Neural Networks Actually Learn

This paper introduces the use of Representation Conditional Diffusion Models (RCDM) to visualize what self-supervised learning (SSL) models

Theoretical Foundations of Deep Learning

Vision fine-tuning overview

New preprint: