I’m starting to do research in an area of ML that is new to me. After a few weeks of digging and reading, I’ve identified around 20-30 important papers in this area. I’m trying to find the most efficient way (in terms of speed vs knowledge retained) to read, understand, and retain these papers.

Does anyone here have any strategies/templates they use in these circumstances?

So far, I’m thinking:

– 1 markdown/latex file per paper with abstract + my own bullet point notes

– A mindmap or some similar visualization that connects all the papers

– Storing this along with the pdfs of the papers as a git repo to make navigation easy

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Looking for both reading/understanding strategies as well as summarization/organization ones.