Explore the intersection of deep learning and causality in this 26-minute conference talk by Rahul Krishnan at the Computational Genomics Summer Institute (CGSI) 2024. Delve into cutting-edge research bridging the gap between these two crucial fields, with insights drawn from recent papers on sequential decision-making, structured neural networks for density estimation and causal inference, and partial identification of treatment effects. Gain valuable knowledge on how deep learning techniques can be applied to causal inference problems, potentially revolutionizing approaches in computational genomics and beyond.