I'm finding this list up to 2016 rather useful:https://github.com/terryum/awesome-deep-learning-papers …
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Curious: how are people finding the most important recent AI papers? (I haven't been seriously following, but would like to catch up.)
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@karpathy's arxiv-sanity is a great project, and I wondered how the top papers over the past year (http://www.arxiv-sanity.com/top?timefilter=year&vfilter=all … ) would be. But many of the most-saved papers are elementary tutorials, which makes me wonder about the collective(!) judgement of users on the siteShow this thread -
What are your favourite 1-3 AI / ML papers over the past 12-24 months? (And feel free to say what excited you about them?)
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(To clarify the arxiv-sanity remark: nothing against the project or users! But it suggests the collective judgements are from people fairly new to the field - natural, given the influx into deep learning. But curious about the recommendations of ppl who've been at this a while!)
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The suggestions so far are great! Please keep them coming! Also love to hear about classic papers that you particularly like!
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These days I find better use of my time reading dated papers that are considered important now, but perhaps not considered important when they were published. If you like RL, the OpenAI project announced today has nice curated list: https://spinningup.openai.com/en/latest/spinningup/keypapers.html …https://twitter.com/jachiam0/status/1060587899861688320 …
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Thanks! (In general, in areas I know well, I prefer reading old papers, often very old papers. But I haven't really tried to keep track of AI / ML / DL at all, so I'm sorta catching up.)
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