This has been a really fun one! challenging the wisdom that one needs a lot of data to do ML guided biodesign. In fact, if you have to choose, think about getting HQ small-N data aligned w your endpoint, vs HT proxy data. low-N ML now helps you succeed w the former!https://twitter.com/grigonomics/status/1220768850834284544 …
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For the ML folks reading this, we're excited by the extreme data-efficiency we saw here, and for forward design of a complicated natural object no less. Another feather in the cap of unsupervised/semi-supervised learning, no doubt!
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As always, inspiring to work with and learn from
@grigonomics and@EthanAlley, and have the mentorship of@kesvelt and@geochurch :)1 reply 0 proslijeđenih tweetova 4 korisnika označavaju da im se sviđaPrikaži ovu nit
Hope you enjoy the read! We haven't submitted this anywhere yet so feedback and venue/journal suggestions welcome! DMs open
11:35 - 24. sij 2020.
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- a framework for low-N protein engineering with data-efficient deep learning! Had a blast working with brilliant