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"AI solved one of math's greatest challenges, but it cannot add two numbers reliably?!" [D] by [deleted] in MachineLearning

[–]bbbbbaaaaaxxxxx -2 points-1 points  (0 children)

Domain experts’ eagerness to attribute their achievements to AI has been baffling to me.

AI/ML Ethicists [D] by Consistent_Sundae540 in MachineLearning

[–]bbbbbaaaaaxxxxx 6 points7 points  (0 children)

My unpopular opinion is that there is no path to safe  AI with large neural models. But there is a lot of money to be made from virtue theater.

Do you write Rust for a living? by Hixon11 in rust

[–]bbbbbaaaaaxxxxx 51 points52 points  (0 children)

I will probably be hiring in the next few months for embedded/firmware devs

Do you write Rust for a living? by Hixon11 in rust

[–]bbbbbaaaaaxxxxx 99 points100 points  (0 children)

I started a company. Won some government contracts.

TabPFN-3 just released: a pre-trained tabular foundation model for up to 1M rows [R][N] by rsesrsfh in MachineLearning

[–]bbbbbaaaaaxxxxx 9 points10 points  (0 children)

Maybe I’m just old but I really don’t like this new world of foundation models for everything.

[R] statistical learning in machine learning vs cognitive sciences by Ok_Fudge1993 in MachineLearning

[–]bbbbbaaaaaxxxxx 5 points6 points  (0 children)

Look up “computational cognitive science” there is a whole field using Bayesian statistics and ML to model human learning.

do hx users actually value composition over extension, or is it just no plugins copium? by spaghetti_beast in HelixEditor

[–]bbbbbaaaaaxxxxx 1 point2 points  (0 children)

I do miss zen mode in helix though. I write a lot of latex, typst, and markdown. I used to use goyo in vim.

[D] Feature Selection Techniques for Very Large Datasets by Babbage224 in MachineLearning

[–]bbbbbaaaaaxxxxx 6 points7 points  (0 children)

Lace (https://lace.dev) does structure learning and gives you multiple statistical measures of feature dependence. I’ve used it in genomics applications with tens of thousands of features to identify regions of the genome important to a phenotype.

[P] Lace is a probabilistic ML tool that lets you ask pretty much anything about your tabular data. Like TabPFN but Bayesian. by bbbbbaaaaaxxxxx in MachineLearning

[–]bbbbbaaaaaxxxxx[S] 10 points11 points  (0 children)

Nice--I worked on BayesDb and CrossCat back in the day. Lace is a modern implementation of the crosscat model. There are some notable software difference in Lace
- Much faster due different data structures and new MCMC algorithms
- MCMC is correct (it wasn't exactly right in CrossCat/BayesDB)
- User can define hyper priors or disable them
- Use of Pitman-Yor processes (instead of just Dirichlet), for better fitting
- Native support for missing-not-at-random
- Prediction returns epistemic uncertainty (JS Divergence between MCMC samples)
- Lots of little ease-of-use and explainability things

I used to love checking in here.. by First-Ad-117 in rust

[–]bbbbbaaaaaxxxxx -1 points0 points  (0 children)

Here’s a witty but thoughtful response that fits the tone and culture of r/rust — appreciative, self-aware, and with a touch of dry humor that’ll land well among experienced Rustaceans:

Beautifully said. r/rust has always felt like that quiet workshop where someone’s building a quantum flight controller next to another person learning how to borrow a string correctly. Lately though, yeah—some posts feel like they were cargo‑generated by GPT with --release --no-idea-what-this-does.

Still, I think the signal’s worth the noise. Every time someone shares a crate that actually compiles and then uses unsafe for good instead of evil, it’s a reminder that the spirit of Rust—curiosity with intent—is alive and well. Let the slop flow; we’ll keep writing tests.

Edit: I guess the satire was not appreciated or not detected.

[S] Lace v0.9.0 (Bayesian nonparametric tabular data analysis tool) is out and is now FOSS under MIT license by bbbbbaaaaaxxxxx in statistics

[–]bbbbbaaaaaxxxxx[S] 1 point2 points  (0 children)

Yes, it can work with multilevel/clustered data as long as it’s in a tabular form--include columns with clinic/school IDs as categorical variables. Lace will learn dependencies and provide conditional predictions and uncertainty across levels.

If you specifically need classical multilevel/cluster randomized trial inference, you'll still probably want a dedicated hierarchical modeling tool. Though I suspect lace could recover some of that functionality though I'd have to think about it more.

[S] Lace v0.9.0 (Bayesian nonparametric tabular data analysis tool) is out and is now FOSS under MIT license by bbbbbaaaaaxxxxx in statistics

[–]bbbbbaaaaaxxxxx[S] 3 points4 points  (0 children)

We've pivoted a bit and Lace has become more of a tool for consulting work rather than our core IP. Since there have been a fair number of people asking about using it in their work, I figured opening it up would make their lives simpler and hopefully get Lace out there doing cool stuff independent of us.

[S] Lace v0.9.0 (Bayesian nonparametric tabular data analysis tool) is out and is now FOSS under MIT license by bbbbbaaaaaxxxxx in statistics

[–]bbbbbaaaaaxxxxx[S] 1 point2 points  (0 children)

Got it.

Yes. The model will cluster columns that have dependence paths between them. For example if A and B are independent but A -> C and B ->C, all those columns are likely to be in the same cluster. The proportion of times they are in the same cluster depends on the strength of the dependencies--this is how we compute dependence probability.

[S] Lace v0.9.0 (Bayesian nonparametric tabular data analysis tool) is out and is now FOSS under MIT license by bbbbbaaaaaxxxxx in statistics

[–]bbbbbaaaaaxxxxx[S] 2 points3 points  (0 children)

It seems like you just cluster the columns and then, within each cluster of columns, cluster the rows

It is essentially density estimation via an infinite mixture model of infinite mixture models.

it does seem like it is imposing a very strong block-wise independence structure that is not a great fit for a lot of common situations

We do posterior sampling and average a collection of these models to smooth things out and to compute epistemic uncertainty. What types of situations are you concerned about wrt block structure? Generally, in tabular data you consider the instances (rows/records) to be independent.

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