On Feb 9, Jonas Arruda and @alex-andorra.bsky.social will give a live demo on diffusion models for SBI using BayesFlow. Don't miss out! www.linkedin.com/feed/update/...

Diffusion Models in Python: Live Demo with Alexandre Andorra | Alexandre Andorra

📢 Big News: We are going LIVE with code! Diffusion models aren't just for generating images -- they are a powerful tool for scientific inference. On Feb 9, I’m hosting Jonas Arruda on the Learning Ba...

linkedin.com

I defended my PhD last week ✨ Huge thanks to: • My supervisors @paulbuerkner.com @stefanradev.bsky.social @avehtari.bsky.social 👥 • The committee @ststaab.bsky.social @mniepert.bsky.social 📝 • The institutions @ellis.eu @unistuttgart.bsky.social @aalto.fi 🏫 • My wonderful collaborators 🧡 #PhDone 🎓

What advice do folks have for organising projects that will be deployed to production? How do you organise your directories? What do you do if you're deploying multiple "things" (e.g. an app and an api) from the same project?

Amortized inference for finite mixture models ✨ The amortized approximator from BayesFlow closely matches the results of expensive-but-trustworthy HMC with Stan. Check out the preprint and code by @kucharssim.bsky.social and @paulbuerkner.com👇

BayesFlow@bayesflow.org · last yr.

Finite mixture models are useful when data comes from multiple latent processes. BayesFlow allows: • Approximating the joint posterior of model parameters and mixture indicators • Inferences for independent and dependent mixtures • Amortization for fast and accurate estimation 📄 Preprint 💻 Code

Finite mixture models are useful when data comes from multiple latent processes. BayesFlow allows: • Approximating the joint posterior of model parameters and mixture indicators • Inferences for independent and dependent mixtures • Amortization for fast and accurate estimation 📄 Preprint 💻 Code

If you know simulation based calibration checking (SBC), you will enjoy our new paper "Posterior SBC: Simulation-Based Calibration Checking Conditional on Data" with Teemu Säilynoja, @marvinschmitt.com and @paulbuerkner.com arxiv.org/abs/2502.03279 1/7

A study with 5M+ data points explores the link between cognitive parameters and socioeconomic outcomes: The stability of processing speed was the strongest predictor. BayesFlow facilitated efficient inference for complex decision-making models, scaling Bayesian workflows to big data. 🔗Paper

Join us this Thursday for a talk on efficient mixture and multilevel models with neural networks by @paulbuerkner.com at the new @approxbayesseminar.bsky.social!

Approximate Bayes Seminar@approxbayesseminar.bsky.social · 2y ago

A reminder of our talk this Thursday (30th Jan), at 11am GMT. Paul Bürkner (TU Dortmund University), will talk about "Amortized Mixture and Multilevel Models". Sign up at listserv.csv.warwick... to receive the link.

Paul Bürkner (TU Dortmund University), will give our next talk. This will be about "Amortized Mixture and Multilevel Models", and is scheduled on Thursday the 30th January at 11am. To receive the link to join, sign up at listserv.csv.warwick...

Paul Bürkner (@paulbuerkner.com) will talk about amortized Bayesian multilevel models in the next Approximate Bayes Seminar on January 30 ⭐️ Sign up to the seminar’s mailing list below to get the meeting link 👇

Approximate Bayes Seminar@approxbayesseminar.bsky.social · 2y ago

Paul Bürkner (TU Dortmund University), will give our next talk. This will be about "Amortized Mixture and Multilevel Models", and is scheduled on Thursday the 30th January at 11am. To receive the link to join, sign up at listserv.csv.warwick...

More than 60 German universities and research outfits are announcing that they will end their activities on twitter. Including my alma mater, the University of Münster. HT @thereallorenzmeyer.bsky.social nachrichten.idw-online.de/2025/01/10/h...

Hochschulen und Forschungsinstitutionen verlassen Plattform X - Gemeinsam für Vielfalt, Freiheit und Wissenschaft

nachrichten.idw-online.de

what are your best tips to fit shifted lognormal models (in #brms / Stan)? I'm using: - checking the long tails (few long RTs make the tail estimation unwieldy) - low initial values for ndt - careful prior checks - pathfinder estimation of initial values still with increasing data, chains get stuck

OK, here is a very rough draft of a tutorial for #Bayesian #SEM using #brms for #rstats. It needs work, polish, has a lot of questions in it, and I need to add a references section. But, I think a lot of folk will find this useful, so.... jebyrnes.github.io/bayesian_sem... (use issues for comments!)

Ternary plots to represent data in a simplex, yay or nay? #stats #statistics #neuroscience

Writing is thinking. It’s not a part of the process that can be skipped; it’s the entire point.

Anna E. Clark@annaeclark.bsky.social · 2y ago

This is what's so baffling about so many suggestions for AI in the humanities classroom: they mistake the product for the point. Writing outlines and essays is important not because you need to make outlines and essays but because that's how you learn to think with/through complex ideas.

1️⃣ An agent-based model simulates a dynamic population of professional speed climbers. 2️⃣ BayesFlow handles amortized parameter estimation in the SBI setting. 📣 Shoutout to @masonyoungblood.bsky.social & @sampassmore.bsky.social 📄 Preprint: osf.io/preprints/ps... 💻 Code: github.com/masonyoungbl...

Kyle Cranmer@kylecranmer.bsky.social · 2y ago

One of the most surprising uses of simulation-based inference: agent based models of olympic speed climbers osf.io/preprints/ps...

Neural superstatistics are a framework for probabilistic models with time-varying parameters: ⋅ Joint estimation of stationary and time-varying parameters ⋅ Amortized parameter inference and model comparison ⋅ Multi-horizon predictions and leave-future-out CV 📄 Paper 1 📄 Paper 2 💻 BayesFlow Code

“We don’t value software, data, and methods in the same way we value papers, even though those resources empower millions of scientists” 💯 www.statnews.com/sponsor/2024...

New report highlights the scientific impact of open source software

Two of the scientists who won this year’s Nobel Prize for cracking the code of proteins’ intricate structures relied, in part, on a series of computing

statnews.com

The public beta version of Positron was released almost 6 months ago, and the team certainly hasn’t been idle! So what happened over the last half year? Is it worth switching? 👀 I definitely like where it's heading! Personal highlights: data explorer, command palette, help on hover + extensions 👇🏻📚

I'm going to have time to do 1-2 contributions for the summer 25 release. Here's my list to choose from, what is most interesting to you? - adding lower/upper bounds to ordered vectors (removing positive ordered since it's achieved by lb=0)

Sean Pinkney@spinkney.bsky.social · 2y ago

A new release of Stan is coming discourse.mc-stan.org/t/cmdstan-st.... Highlights: New constraints for stochastic matrices and zero-sum vectors Easier user-defined constraints Improved diagnostics New distribution, beta_negative_binomial

Prior specification is one of the hardest tasks in Bayesian modeling. In our new paper, we (Florence Bockting, @stefanradev.bsky.social and me) develop a method for expert prior elicitation using generative neural networks and simulation-based learning. arxiv.org/abs/2411.15826

Expert-elicitation method for non-parametric joint priors using normalizing flows

We propose an expert-elicitation method for learning non-parametric joint prior distributions using normalizing flows. Normalizing flows are a class of generative models that enable exact, single-step...

arxiv.org

I'm writing up a brief history of the tidyverse? What do you want to know about it? #rstats

Any single analysis hides an iceberg of uncertainty. Sensitivity-aware amortized inference explores the iceberg: ⋅ Test alternative priors, likelihoods, and data perturbations ⋅ Deep ensembles flag misspecification issues ⋅ No model refits required during inference 🔗 openreview.net/forum?id=Kxt...

I feel like not enough people know about Quarto for creating documents. How it works: Write in markdown and use Quarto to convert it to html, pdf, epub, ... I produce my books with Quarto (web + ebook + print version). But you can also use it for websites, reports, dashboards, ... quarto.org

Quarto

An open source technical publishing system for creating beautiful articles, websites, blogs, books, slides, and more. Supports Python, R, Julia, and JavaScript.

quarto.org

Optimist: The cup is half full Pessimist: The cup is half empty Frequentist: *takes a deep breath* The probability that the cup is half full given the observed volume of water (or more extreme volumes) is larger than 5% so I cannot reject the null hypothesis that the cup is half full.

Michael "Shapes Dude" Betancourt@betanalpha.bsky.social · 2y ago

Optimist: The cup is half full Pessimist: The cup is half empty Bayesian:

Optimist: the cup is half full Pessimist: the cup is half empty Comparative cognition researcher: I wonder if this animal will drop some stones into this cup

samuel mehr@mehr.nz · 2y ago

Optimist: the cup is half full Pessimist: the cup is half empty Developmentalist: even when I demonstrate that the taller cup holds the same amount of water as the wider cup, this kid thinks the tall one has more

Ladies and gentlemen... the weekend. (also: you are important and are not alone 🧡)

BayesFlow is a library for amortized Bayesian inference with neural networks. ⋅ Multi-backend via Keras 3: Use PyTorch, TensorFlow, or JAX. ⋅ Modern nets: Flow matching, diffusion, consistency models, normalizing flows, transformers ⋅ Built-in diagnostics and plotting 🔗 github.com/bayesflow-or...

The ✨ML Internship Feed✨ is here! @serge.belongie.com and I created this feed to compile internship opportunities in AI, ML, CV, NLP, and related areas. The feed is rule-based. Please help us improve the rules by sharing feedback 🧡 🔗 Link to the feed: bsky.app/profile/did:...

The brand new `legendry` package by @teunbrand.bsky.social takes ggplots2 guides to the next level 🤩 teunbrand.github.io/teunbrand_bl...