This repo is a collaborative effort to TLDR; all the ML in Drug Discovery papers. This page is the HOWTO, you can find TLDRs here.
There are lots of humongous paper lists, the reading stack grows every day, but it's hard to read everything, and even click on everything. This repo provides short TLDRs that help us to choose candidates for the reading list or to pass on if we are not interested. This also provides a structured and easily parseable document for further use with your scripts or your favourite ML algorithm.
Grab a template below, add the TLDR; to the bottom of the list, and send a PR with your favourite paper. Another way to help is to refine an existing TLDR. If you feel like refining some entries, go for it!
- TLDR ID: n+1, where n is the current number of papers in the TLDR list
- List authors here
- Venue
- Link to the paper
- Implementations:
What is being proposed?
What is the motivation behind the paper?
Add the one-two sentence conclusion here.