The amazing Bernard Koch (Bernie) just posted on Arxiv "Deep Learning of Potential Outcomes". If you're either familiar with causality but not with deep learning, or the other way around, this is a great place to start! arxiv.org/abs/2110.04442

And, to make things even better, the review paper is accompanied by a detailed tutorial in TensorFlow 2, so you can try it by yourself! github.com/kochbj/Deep-Le…

Pablo Geraldo B. Thanks for sharing beyond my loyal 13 followers Pablo. :) I'd just add that this literature is exciting because it provides interesting directions not just for heterogeneous effect estimation, but also CI with text, graphs, and images!

Wow! Honored that our paper with Bernie Koch, Remi Denton, and Jacob Foster won a best paper award at the NeurIPS Dataset and Benchmark track! So pleased that a sociology of science paper won such an honor at NeurIPS. blog.neurips.cc/2021/11/30/ann…