dccsillag

4 ms·

1.
by dccsillag 6mo ago
I'm sorry, but what exactly is the problem with the code? I've been staring at it for quite a while now and still don't see what is counterintuitive about it.
2.
by dccsillag 1y ago
Take enough moments and you'll be able to differentiate any distributions.
3.
by dccsillag 1y ago
I think you vastly overestimate the capacity of Python typing.
4.
by dccsillag 1y ago
Typing still sucks big time. Same for perf, unless you are working with numerics that fit with something like NumPy or JAX.
5.
by dccsillag 1y ago
No, it's generally not valid -- it will depend on the specifics of the test (especially if the test is valid only asymptotically). You need some method that supports sequential inference. Nowadays your best bet is probably some sort of
6.
by dccsillag 1y ago
Hard disagree. There are a lot of implementation "details" that, if you want to do properly, are a lot of hard work and very much nontrivial. For example, do try to write a compiler with efficient incremental compilation, and espe
7.
by dccsillag 2y ago
I've never seen this done in a research setting. Not sure about how much of a standard practice it is.
8.
by dccsillag 2y ago
It has `catch_unwind` [1], but that still retains the panicking runtime, so not sufficient in the context of the post. [1] https://doc.rust-lang.org/std/panic/fn.catch_unwind.html
9.
by dccsillag 2y ago
Yeah, I'm fairly sure that there is such a flag/toplevel attribute... and if there isn't, there should be one. It also feels like most of the pains on avoiding panics centers around allocations which, though a bit unfortunate
10.
by dccsillag 2y ago
Can we please rename this submission? This is excessively grandiose, way over the top......
11.
by dccsillag 2y ago
If I'm not mistaken, the treatment of forward declarations proposed in the article actually breaks the C standard, which would be a rather pressing concern. As far as I am aware, that is the reason why things are the way they are rig
12.
by dccsillag 2y ago
If thresholding of P-values is the issue, E-values -- a recent, much more elegant, easier to work with, and more robust alternative to P-values -- solve this. https://arxiv.org/abs/2312.08040 https://arxiv.o
13.
by dccsillag 2y ago
I've used Quiver a number of times now, and all of them were great experiences. Kudos to the authors!
14.
by dccsillag 2y ago
(Side note) That's odd, lobste.rs seems to be down for me, and has been like that for a couple of months now -- I literally cannot reach the site. Is that actually just me?? EDIT: just tried some things, very weird stuff: curl works fi
15.
by dccsillag 2y ago
Well, yes, but that's an extremely low bar!!
16.
by dccsillag 2y ago
I find it odd that all of the mathematicians cited at the end are actually pretty much CS people, working on proof assistants. Kinda renders that section pointless, IMO (though the comment by Isabelle's author was interesting). IMO, wh
17.
by dccsillag 2y ago
Theory-wise, I'm not convinced that the models have good approximation properties (the Kolmogorov-Arnold / Kolmogorov Superposition Theorem they base themselves on has quite a bit of nuance), and the optimization problem might be
18.
by dccsillag 2y ago
Ah, Kolmogorov Arnold Networks. Perhaps the only model I have ever tried that managed to fairly often get AUCs below 0.5 in my tabular ML benchmarks. It even managed to get a frankly disturbing 0.33, where pretty much any other method (incl
19.
by dccsillag 2y ago
Yeah, I know the account you are talking about, it really is a bit over the top. It's a shame, I've met a bunch of people who mentioned that they were actually turned away from Conformal Prediction due to them. > But having sai
20.
by dccsillag 2y ago
That's a particular form of Conformal Prediction, called Split Conformal Prediction. Incidentally, it's also one of the best ones (i.e., most extensible, strongest guarantees, easiest to implement, remarkably sample-efficient). Ma
21.
by dccsillag 2y ago
Bayesian Neural Networks just seem like a failed approach, unfortunately. For one, Bayesian inference and UQ fundamentally depends on the choice of the prior, but this is rarely discussed in the Bayesian NN literature and practice, and is f
22.
by dccsillag 2y ago
And the potential outcomes framework (Neyman-Rubin) is even more general :) Either way, Holland's 'Statistics and Causal Inference' paper (1986) is a nice read on the different frameworks for causality, especially in regards
23.
by dccsillag 3y ago
> All know 20 year old latex documents will be compilable in 20 years. Except it's not. For example, in 2021, the NeurIPS template compiled differently in different versions of TeXLive ( https://tex.stackexchange.com/
24.
by dccsillag 3y ago
Because a library in a programming language would be madly inconvenient? I can't see something like this being pleasant to use: document( paragraph("blah blah blah"), math("sum_(i=1)^n i = (n (n+1))/2&qu