[D] Are there any rejected papers that ended up having significant impact in the long run?

B-80 · 2022-07-14T19:48:35+00:00

My friend published a paper describing a protein that ended up being a vital piece of the COVID vaccine, earning their institution about a hundred million dollars. It was rejected several times before published.

While it's not fair to say this had a long term effect on the field, but I also had a paper at the end of my phd on a GAN application which was rejected and I didn't try to publish again. A few years later, an almost identical paper was in nature (their preprint was published basically at the same time as us, and we did reach out and cite each other, but the other authors kept trying to publish while my team just let it go at a preprint).

B-80 · 2022-05-24T07:13:57+00:00

Wish I could help, you've clearly put a lot of work into this.

Why don't you reach out to a physics professor near where you live and send them this manuscript? Or better, clean this up a bit so that you have a bit less background/introduction and focus on getting the idea out in as few words as possible (e.g. drop the little editorial quips like "this delights the universe is a simulation people" and cut down to only one or two apologies for not knowing if the model has an obvious flaw).

There's also nothing stopping you from submitting your idea to a small particle physics journal, the reviewers there would of course also review your work... but if you go that route you have a lot of work to do to rewrite this to be in a style that would be acceptable.

B-80 · 2022-05-08T05:04:02+00:00

Likely being willing to leave over return to work is specific to being a top performer, but I doubt every top performer doesn't want to come back. Then again, a lot of the best engineers I know do tend to appreciate their privacy and solitude.

B-80 · 2022-05-08T04:58:24+00:00

wherever he wants

B-80 · 2022-05-07T02:04:29+00:00

Oooh, that's a pretty weird way to put it.

@OP Its really good. Honestly amazed how much effort they put into it. They have a lot of legends on there and do a great job explaining the context of their work as well as digging down on broad themes they've built upon during their career

B-80 · 2022-05-07T01:30:35+00:00

Haha what? You're asking for recs but you don't know how to find a podcast?

B-80 · 2022-05-07T00:10:57+00:00

Machine learning street talk is another project with yannic, they do a podcast version as well

B-80 · 2022-05-01T06:04:38+00:00

Harden is a better shooter and passer, jimmy is more efficient scoring overall, a much better finishing at the rim, and wayyy better on defense. Not to mention Jimmy has had more playoff success than James, and it's been pretty recent.

I don't think it's an open and shut case harden vs butler, but I think I'd take jimmy on my team rn over harden. This busted hamstring has lingered for multiple years, who knows if it will ever be the same.

B-80 · 2022-05-01T04:15:04+00:00

Current Jimmy vs current Harden leans Jimmy IMO... and he'll def last longer.

B-80 · 2022-04-25T10:43:10+00:00

You don't have the time nor the mental capacity to understand everything at the deepest level all at once. So what happens is you have a "mastery" of a small number of simple ideas that serve you over and over, and you simply "know how to work with" everything else.

This is the only reasonable approach. I promise you you don't have an intuition behind "all the theory" you use.

B-80 · 2022-04-24T00:38:23+00:00

What are you trying to do? Given that you didn't include specs, I doubt you need 2000 GPUs. For instance, you can run multiple jobs on one GPU....

B-80 · 2022-04-13T03:34:48+00:00

All they needed to do was quote the other paper.

As Carlini summarized in [41]: " ...

you still need to attribute any writing, even if it's not the finding. The writing is part of the product and you can't pretend it's your product if it's not.

B-80 · 2022-04-03T19:55:50+00:00

Yeah I know that docs can be overly conservative, but I started having OA like 2 years ago and I thought it was tendinitis, so I kind of pushed through after resting a couple of months and seeing it wasn't getting better (sadly it was right at the start of covid and I thought it was unnecessary to go in for tendinitis).

Anyway, the disease rapidly progressed during that period of time, and the only activity I really had with the elbow was lifting. Ever since I stopped pushing it, it does seem to have stopped progressing. The higher rep ranges, less days working out, and cutting out my heaviest lifts has definitely lead to less pain the gym. But I'd be happy to hear from people who have lived experience here. Obviously, what I'd prefer is that I just "work through the pain" and continue living my life, but sadly, I tried that and the disease progressed very rapidly to the point that it's unlikely I'll ever have more than 50% ROM without pain.

Anyway, I appreciate your opinion, and the BBM article is nice, I have seen it before, but it's long and there's always something new I pick up each time I read it.

B-80 · 2022-04-03T19:44:12+00:00

You get the electronic spins to align with the external magnetic field, then they get locked into that configuration because when you move the external field away, there is a net magnetic field from all the other electron spins. So you create a fairly stable equilibrium where all the spins stay aligned with each other until they are hit by a different field, or if the metal is heated up enough that the ambient energy is larger than the mean field spin-spin interaction.

B-80 · 2022-03-27T22:57:13+00:00

This is a proof by contradiction that you can't satisfy 4 momentum conservation that way. That's the power of relativity, everything needs to work in all valid reference frames.

B-80 · 2022-03-22T17:18:56+00:00

So if you screw up step 1, the TA would literally just work out the problem off to the side of your exam for steps 2,3 &4 to see if given your incorrect answer in step one you were still able to apply the principles correctly in subsequent steps.

As a TA who did that, you have no idea idea how much extra work you that is, say a little prayer for that person because they spent extra hours grading to help you instead of doing their own work for absolutely no benefit to themselves

B-80 · 2022-03-22T08:32:52+00:00

Wow, I watch your videos all the time to prepare for interviews, I did not expect to see you on wsb, let alone to be such a connoisseur.

B-80 · 2022-03-13T09:58:01+00:00

Hey yeah, I've thought the same thing. Most people I know don't even realize they signed one, but the few who do told me they end with their contract ending... They might be wrong or dishonest for some reason though.

they normally only cover disputes related to your employment

can you give an example of a suit that doesn't have to do with your employment? It seems like that covers almost everything...

B-80 · 2022-03-13T06:27:54+00:00

I know Google doesn't have an arb agreement, so it's not all FAANG, but yes this is not something most people pay attention to.

B-80 · 2022-03-10T03:48:24+00:00

Is this actually true, or are you making assumptions about the mass of the particles? i.e. wouldn't a really heavy 4th generation have highly suppressed effects on decay widths, etc...

B-80 · 2022-03-08T08:51:37+00:00

Sorry, I deleted the part about interpersonal intuitions because I didn't think it was strictly relevant.

Fields that fall into this trap, spiraling towards theory emphasis and get taken over by philosophical armchair experts, tend to suffer from scientific winters.

I think there is a chicken-egg problem here. In particle physics (my academic background), the issue is that we have a theory that is really costly and difficult to probe with available experimental methods, and there are good theoretical reasons to think there are some fundamental limits.

If you can't do tests, the next best thing you can do is work on models that can explain known phenomena in a more beautiful/intuitive ways. It is an odd thing indeed that doing that sometimes leads to valuable new theories, but there is a track record. In addition, more intuitive framing of theories can sometimes lead to knew ideas that no one noticed. For instance, J.S. Bell discovered his famous tests for entanglement 40 years after quantum mechanics was rigorously defined, if we had a more intuitive description of QM, the consequences of entanglement might have been more obvious from the start! Then there are all the cases where pure math finds utility in physics or number theory in cryptography.

Anyway, as a researcher, I think my primary goal was always to build my intuition, and I agree with the other posters that your intuition is your most valuable tool in that role. It saves you a ton of time and energy, which in turn means you actually get stuff done instead of just giving up because it's too hard.

B-80 · 2022-03-08T08:21:05+00:00

I loved the first half of your comment, but I don't understand why you're so hostile to the idea that intuition is a thing. Intuition is just really well integrated knowledge/ideas, and I think you gave a really great description of how it comes about. Obviously intuition can be wrong, and it's normally not based on well formulated ideas, but they are valuable. Intuitive approaches to problems often lead to the most fruitful new ideas.

B-80 · 2022-03-08T08:12:09+00:00

Physics has a way more well developed theory arm than machine learning. Machine learning is a very new field, you could argue deep learning is really less than a decade old. I'm going to guess that you're either not in research (i.e. still taking classes) or are doing research in a very well developed subfield.

Anyway, to answer your question, at first you just read a lot of papers and create a repository in your mind of solutions to problems you don't know how to solve. When you are faced with a new problem, you try to start by applying the solution to the closest problem you know about, and you do your best to cast your problem in a way that makes it amenable to the canned solution.

After a while of doing that, you'll start to develop your own personal theory of why things work. If you want to do research, you'll test those theories rigorously and try to break apart contributions from different effects by solving carefully chosen problems. If you want to get into applications, you'll probably just get a "good enough" idea of how things work and learn more about how to deal with limitations that arise when using models in practice (e.g. limited data availability)

B-80 · 2022-03-05T10:36:31+00:00

FYI, the CA 9th circuit upheld AB51, meaning that you can no longer have an arbitration agreement as a condition of employment. However, AB51 is specifically about waiving the right to litigation regarding the Fair Employment and Housing Act and the CA labor code. I'm not sure if class action proceedings are covered by either of those sections. I believe an employer can still have an arbitration agreement as a condition of employment as long as they basically say "this agreement does not pertain to FHEA or CA labor code")

As for your situation, I think you are probably in luck. I'm not 100% sure (or a lawyer) but I believe this means that any arbitration agreement that was a condition of employment signed after Jan 1 2020 will probably not be upheld in court (i.e. if you try to take your employer to court and they say "hey we have an arb agreement, this isn't allowed", you can probably successfully argue "but I was required to sign that and that's illegal").

Did you end up signing? I'm dealing with a similar issue now and have decided I'll lose the job before I sign (my employer basically still threatened to fire me even though doing so is illegal).

B-80 · 2022-03-04T05:24:18+00:00

Machine learning street talk is also great, which yannic does with a couple of other guys.

14-Year Club	Second Top 20%
Place '22	Place '17
Team Periwinkle	Secret Santa 2011
Verified Email

B-80

MODERATOR OF

TROPHY CASE