AI Paper Recommendations from Experts

After the'top AI books' reading list was so well received, we reached out to some of our community to find out which papers they believe everyone should have read! All of the below papers are free to access and cover a range of topics from Hypergradients to modeling yield response for CNNs. Each expert also included a reason as to why the paper was picked as well as a short bio. We spoke to Jeff back in January and at that time he couldn't pick just one paper as a must-read, so we let him pick two. This paper unpacks two key talking points, the limitations of sparse training data and also if recurrent networks can support meta-learning in a fully supervised context.