#probprog — Public Fediverse posts

Just an extremely well written paper on an extremely interesting little experiment in probabilistic programming + some great self reflection. 10/10 no comments.
Gauguin, Descartes, Bayes: A Diurnal Golem’s Brain
https://dl.acm.org/doi/pdf/10.1145/3759429.3762631
#stats #probprog

I got a Probabilistic Programming starter pack going. Hit me up if you're involved with #probprog R&D and want in! go.bsky.app/JfvubEf

RE: https://bsky.brid.gy/convert/ap/at://did:plc:6ls7x4kw3wsz2opik4wobgkm/app.bsky.graph.starterpack/3lbcssvf7yz2x

@junpenglao @avehtari @mcmc_stan @pymc @TuringLang While I loved all the panelists' answers, in answer to the question, "how will probabilistic programming evolve in the future?", I'd say let's do better at automating what can be automated. IMO users shouldn't have to think about vectorizing their models, marginalizing out discrete parameters, or reparameterizing to improve geometry. This takes valuable time away from the real work of thinking about the question, model, and data. #ProbProg

Great panel on probabilistic programming at #BayesComp2023 with Mitzi, Tor, @junpenglao, and @henri_pesonen and led by @avehtari #probprog
@mcmc_stan @pymc @TuringLang

If you're at #BayesComp2023 and see me, say hi! I especially like talking about #ProbProg, #JuliaLang, @TuringLang, @ArviZ, and how bad I am at skiing!

Tonight I'm presenting a poster about using Pathfinder.jl to initialize HMC and diagnose computational issues.

🚨 New #JuliaLang package! StanLogDensityProblems.jl is a really basic package that implements the LogDensityProblems.jl interface for @mcmc_stan models, built on BridgeStan.jl. It also integrates with PosteriorDB.jl, which makes it really easy to benchmark a new inference method against a large number of models. #ProbProg #MCMCStan

https://github.com/sethaxen/StanLogDensityProblems.jl

The next minor release of MCMCDiagnosticTools.jl is going to be dope. We've been upgrading its implementations of convergence diagnostics, and it's just about ready to replace the Python ones in ArviZ.jl @ArviZ and the ones currently used by Turing. #JuliaLang #ProbProg

👋 This is my first time attending @NeuripsConf (virtually to reduce carbon emissions).

On Friday I'll join the workshop "Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems," where we have a paper, poster, and lightning talk on GPs for modeling #paleoclimate.

If you're attending and want to chat about #GaussianProcesses, probabilistic programming (#ProbProg), or @ArviZ, ping me!

#NeurIPS2022

Soon Turing.jl users will be able to natively store all sampling outputs in an @ArviZ InferenceData object.

To experiment with the bleeding edge, check out https://github.com/sethaxen/DynamicPPLInferenceObjects.jl!

#TuringLang #JuliaLang #FOSS #ProbProg

Updated some new thoughts regarding the TerpreT problem and my naive solution

https://luxxxlucy.github.io/projects/2021_terpret/index.html

The original TerpreT paper(https://arxiv.org/abs/1608.04428)
discussed solving program induction by gradient based optimization(after making the program differentiable by relaxation ).

#probprog #programsynthesis #neuralnetwork #deeplearning #NeuroSymbolic

Updated some new thoughts regarding the TerpreT problem and my naive solution

https://luxxxlucy.github.io/projects/2021_terpret/index.html

The original TerpreT paper(https://arxiv.org/abs/1608.04428)
discussed solving program induction by gradient based optimization(after making the program differentiable by relaxation ).

#probprog #programsynthesis #neuralnetwork #deeplearning #NeuroSymbolic

Updated some new thoughts regarding the TerpreT problem and my naive solution

https://luxxxlucy.github.io/projects/2021_terpret/index.html

The original TerpreT paper(https://arxiv.org/abs/1608.04428)
discussed solving program induction by gradient based optimization(after making the program differentiable by relaxation ).

#probprog #programsynthesis #neuralnetwork #deeplearning #NeuroSymbolic

Updated some new thoughts regarding the TerpreT problem and my naive solution

https://luxxxlucy.github.io/projects/2021_terpret/index.html

The original TerpreT paper(https://arxiv.org/abs/1608.04428)
discussed solving program induction by gradient based optimization(after making the program differentiable by relaxation ).

#probprog #programsynthesis #neuralnetwork #deeplearning #NeuroSymbolic

Updated some new thoughts regarding the TerpreT problem and my naive solution

https://luxxxlucy.github.io/projects/2021_terpret/index.html

The original TerpreT paper(https://arxiv.org/abs/1608.04428)
discussed solving program induction by gradient based optimization(after making the program differentiable by relaxation ).

#probprog #programsynthesis #neuralnetwork #deeplearning #NeuroSymbolic

Hello Fediverse! This is the official account for the #ArviZ project, providing #FOSS tools for exploratory analysis of #bayesian models!

#introduction #ProbProg #stats #python #JuliaLang

#introduction

I'm Chad. Hello from #Seattle! 👋

Since this is @fosstodon ... My #FOSS work is in #julialang, mostly around #Bayesian modeling and probabilistic programming (#probprog)

This started with Soss.jl, a probabilistic programming language (#PPL). I eventually realized I needed primitives with better composability, and started work on MeasureTheory:
https://github.com/cscherrer/MeasureTheory.jl

That's coming along well - next it's back to PPL, now with Tilde.jl, similar to Soss but a bit more flexible

Hi all, my #introduction:
I'm a prof at #UCLA CS, living in #LosAngeles, and researching #ArtificialIntelligence.

I enjoy bridging #machinelearning with probabilistic and logical #reasoning.
That makes me work on probabilistic programming (#probprog), tractable probabilistic models (e.g., #probcircuit), and #neurosymbolic #AI.

Looking forward to some more authentic discourse about AI on this platform.

With PosteriorDB.jl v0.3.0, it's easier than ever to load #Stan models from posteriordb for sampling with StanSample.jl.

https://github.com/sethaxen/PosteriorDB.jl

#JuliaLang #Bayesian #Statistics #ProbProg #FOSS

I'm looking for work! My current funding runs out soon, so I'm looking for what's next. More contract work? Full-time employment? Something else?

Most of my work has been in #julialang, developing #foss packages for probabilistic programming (#probprog) and #measuretheory. More generally, I'm interested in #bayesian #stats, performance algorithms, composability, and #functionalprogramming. I love learning and #mentoring, and I've been a team lead and IC, enjoying both.

Please retoot!

@BenediktEhinger Welcome! There's a good number of #JuliaLang folks on here as well, and a number of us are into #statistics and #probprog.

I just migrated from @[email protected] to this new account at fosstodon.org, so time for a reintroduction!

I'm a #MachineLearning engineer with a focus on probabilistic programming (#probprog) at @unituebingen, where I help scientists use ML for their research. In the office and out, one of my main passions is #FOSS, and I work on a number of #opensource packages, mostly in #JuliaLang :julia: with a focus on #probprog, #manifolds, and #autodiff.

#introduction

@johnryan Yeah I do #probprog in #JuliaLang, and it's great that we can use arbitrary Julia code within our models. This is because most of the language is differentiable with #autodiff and code is composable, which is not the case for most PPLs.

For #deeplearning research, Julia could come in handy for writing and transforming custom kernels without fussing with CUDA, as some posts in that thread note, but I have no experience with this.

In ArviZ.jl we store inference results (especially #MCMC draws) as InferenceData. It's built on DimensionalData, so we have multidimensional real arrays with named dimensions. Each array element is a marginal of a random draw, which is a useful format for plotting, #statistics, and diagnostics, but sometimes it's useful to get back to a structure more like what a PPL might emit.

Surprisingly, we can get pretty close with just 8 lines of code:
https://github.com/arviz-devs/InferenceObjects.jl/issues/27

#probprog #foss #JuliaLang

Hello fediverse!

I'm a #machinelearning engineer with a focus on probabilistic programming (#probprog) at @unituebingen, where I help scientists use ML for their research. In the office and out, one of my main passions is #FOSS, and I work on a number of #opensource packages, mostly in #JuliaLang, with a focus on #probprog, #manifolds, and #autodiff.

I have no idea what this account will be about, but probably some combination of the above topics. 👋

#introduction

#introduction

I'm Chad. Hello from #Seattle! 👋

Since this is @fosstodon ... My #FOSS work is in #julialang, mostly around #Bayesian modeling and probabilistic programming (#probprog)

This started with Soss.jl, a probabilistic programming language (#PPL). I eventually realized I needed primitives with better composability, and started work on MeasureTheory:
https://github.com/cscherrer/MeasureTheory.jl

That's coming along well - next it's back to PPL, now with Tilde.jl, similar to Soss but a bit more flexible