[HN Gopher] A Survey of Deep Learning for Scientific Discovery ___________________________________________________________________ A Survey of Deep Learning for Scientific Discovery Author : alokrai Score : 53 points Date : 2020-03-27 17:46 UTC (5 hours ago) (HTM) web link (arxiv.org) (TXT) w3m dump (arxiv.org) | jefft255 wrote: | Eric Schmidt, as in Google's ex-CEO, is the second author of this | paper! I didn't know he did any scientific research. | hervature wrote: | He has a PhD, unlike Brin and Page. | jefft255 wrote: | Right, but they both were Ph.D. students and Brin I think | published quite a bit of scientific papers before dropping | out. | throwqwerty wrote: | Looks like a good summary. Will read. But at the rate the | discipline moves I feel like we need one of these every couple of | months for everyone (not just "lay" scientists). Anyone know a | good journal or something that produces a similar sort of survey | frequently? Like once a quarter? | ssivark wrote: | "Rate at which the discipline moves" is mostly churn, not | progress. Important insights come at a slower rate -- at the | speed of human understanding, not at the speed of conference | papers. Good papers from even decades ago are likely to still | be useful -- in fact, they will have the key ideas presented | simply and clearly, without much jargon or hype. Yes, deep | learning practice moves quite fast these days, but that's just | the veneer on top of those deeper ideas, trying out tweaks and | variations. That's not completely an indictment of deep | learning, rather, any nascent field has a lot of confusing | bustle. | biomodel wrote: | Always wonder who these kinds of reviews / surveys are for? | Nobody is going to learn machine learning by reading a 50 page | pdf. Meanwhile, people that have experience will have a hard time | finding the info they don't already know. | | Opinionated & narrow >> Shallow & comprehensive | abdullahkhalids wrote: | They are useful for someone in a nearby field trying to learn | this field. That person first reads the textbook, and a few | specific papers. Then once, they have a good narrow | understanding, they broaden it by reading one of these review | papers. | | In essence, a review paper saves you the trouble of doing a | literature review in a new subfield, because it identifies the | important papers for you. | | That said, the reason review papers are usually written is for | the authors to cement their own understanding of the network of | research in the field. | throwawayjava wrote: | A good review article is worth its weight in gold for both the | researchers who write it and the research community. | | Remember that research communities are extremely transient | because of the professor : phd student : practitioner ratio and | the low odds that a graduated phd student a) stays in research | and then b) stays in the same research area for their whole | career. Therefore, most members of a given research community | have approximately 1-3 years of experience in the broader | academic field and approximately no experience in the area | covered by the review. Therefore, a good review can | simultaneously: | | 1. prevent a lot of wheel re-invention, and | | 2. push the research field in a certain direction (either | accidentally or purposefully). | | Also, good review articles typically include some amount of | synthesis. I.e., the creation of a conceptual framework and | language for understanding and talking about a bunch of vaguely | related stuff. This article tries to do that e.g. in Section | 2.1 but the topic of the review is so incredibly broad that the | categories are not super useful. | antipaul wrote: | In a survey on "scientific discovery", I would have expected more | examples than face and image recognition and natural language | processing, which are so stale at this point. | | Healthcare? Physics? Chemistry? Biology? Sociology? | p1esk wrote: | This is just a bad title. Should have been named simply as "A | Survey of Deep Learning". This paper is an excellent and up to | date overview of deep learning models, methods and best | practices. | wswin wrote: | for the moment I thought it was from 2003 ___________________________________________________________________ (page generated 2020-03-27 23:00 UTC)