iiinova — where your digital self keeps evolving

Reposted by Paul Bürkner

Marvin Schmitt @marvin-schmitt.com · 27/03/2025

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 🎓

Image of a graduating PhD student in the trending Studio Ghibli style.

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Hadley Wickham @hadley.nz · 27/02/2025

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?

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Marvin Schmitt @marvin-schmitt.com · 11/02/2025

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👇

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BayesFlow @bayesflow.org · 11/02/2025

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

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Aki Vehtari @avehtari.bsky.social · 06/02/2025

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

Title: Posterior SBC: Simulation-Based Calibration Checking Conditional on Data

Authors: Teemu Säilynoja, Marvin Schmitt, Paul Bürkner, Aki Vehtari

Abstract: Simulation-based calibration checking (SBC) refers to the validation of an inference algorithm and model implementation through repeated inference on data simulated from a generative model. In the original and commonly used approach, the generative model uses parameters drawn from the prior, and thus the approach is testing whether the inference works for simulated data generated with parameter values plausible under that prior. This approach is natural and desirable when we want to test whether the inference works for a wide range of datasets we might observe. However, after observing data, we are interested in answering whether the inference works conditional on that particular data. In this paper, we propose posterior SBC and demonstrate how it can be used to validate the inference conditionally on observed data. We illustrate the utility of posterior SBC in three case studies: (1) A simple multilevel model; (2) a model that is governed by differential equations; and (3) a joint integrative neuroscience model which is approximated via amortized Bayesian inference with neural networks.

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BayesFlow @bayesflow.org · 03/02/2025

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

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BayesFlow @bayesflow.org · 28/01/2025

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!

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Approximate Bayes Seminar @approxbayesseminar.bsky.social · 14/01/2025

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...

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Marvin Schmitt @marvin-schmitt.com · 14/01/2025

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 👇

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Christian Odendahl @codendahl.bsky.social · 10/01/2025

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...

nachrichten.idw-online.de

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

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Riccardo Fusaroli @fusaroli.eurosky.social · 10/01/2025

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

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Jarrett Byrnes @jebyrnes.bsky.social · 21/12/2024

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!)

jebyrnes.github.io

Full Luxury Bayesian Structural Equation Modeling with brms

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Bruno Hebling Vieira @bhvieira.github.io · 17/12/2024

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

A ternary plot visualizing data points classified into three groups: CN (Cognitively Normal), MCI (Mild Cognitive Impairment), and AD (Alzheimer's Disease dementia). The triangular axes represent predicted probability corresponding to each diagnosis category, with the corners labeled CN (top), MCI (bottom left), and AD (bottom right). Each point is colored according to its real diagnosis group (blue for CN, green for MCI and red for AD). Trajectories of predicted probabilities pertaining to the same subject are denoted with arrows connecting the points. Shaded regions in blue, green, and orange further highlight distinct areas of the plot associated with CN, MCI, and AD, respectively. A legend on the right identifies the diagnosis categories by color.

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Kevin M. Kruse @kevinmkruse.bsky.social · 12/12/2024

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

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BayesFlow @bayesflow.org · 10/12/2024

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...

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BayesFlow @bayesflow.org · 06/12/2024

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

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Robert Aboukhalil @robert.bio · 04/12/2024

“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...

statnews.com

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

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Veerle Eeftink - van Leemput @veerle.hypebright.nl · 03/12/2024

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 👇🏻📚

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Sean Pinkney @spinkney.bsky.social · 02/12/2024

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)

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Paul Bürkner @paulbuerkner.com · 26/11/2024

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

arxiv.org

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...

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Hadley Wickham @hadley.nz · 25/11/2024

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

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BayesFlow @bayesflow.org · 25/11/2024

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...

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Christoph Molnar @christophmolnar.bsky.social · 24/11/2024

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.org

Quarto

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

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Marvin Schmitt @marvin-schmitt.com · 24/11/2024

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.

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Rachael Shaw @wild-minds.bsky.social · 24/11/2024

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

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It's The Weekend 😌 @craigweekend.bsky.social · 23/11/2024

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

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BayesFlow @bayesflow.org · 22/11/2024

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...

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Marvin Schmitt @marvin-schmitt.com · 22/11/2024

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:...

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Jan Broder Engler @jbengler.de · 22/11/2024

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

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Catherine Breslin @catherinebreslin.bsky.social · 22/11/2024

I created two starter packs for Women in AI, as the first filled up 😎 I really hope I’ve added everyone who’s asked to be added, but let me know if you don’t see yourself. Nominations also welcome! go.bsky.app/LaGDpqg go.bsky.app/2wr669L

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Paul Bürkner @paulbuerkner.com · 22/11/2024

Just coming back from an interdisciplinary retreat, and it's kind of crazy how many different ways there are to write down the same linear regression problem.

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Paul Bürkner @paulbuerkner.com · 22/11/2024

The beta version of BayesFlow 2.0 is becoming more powerful and stable by the day. If you are curious about Amortized Bayesian Inference, give BayesFlow a try! github.com/bayesflow-or...

github.com

GitHub - bayesflow-org/bayesflow at dev

A Python library for amortized Bayesian workflows using generative neural networks. - GitHub - bayesflow-org/bayesflow at dev

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Chad Scherrer @cscherrer.bsky.social · 19/11/2024

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

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Motonobu Kanagawa @motonobu-kanagawa.bsky.social · 17/11/2024

We are organising the First International Conference on Probabilistic Numerics (ProbNum 2025) at EURECOM in southern France in Sep 2025. Topics: AI, ML, Stat, Sim, and Numerics. Reposts very much appreciated! probnum25.github.io

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Altmetric @altmetric.com · 18/11/2024

We strongly suggest that academic publishers and other platforms that host research rapidly implement a Share to Bluesky button for their articles. Here's how: docs.bsky.app/docs/advance... #AcademicSky #HigherEd #Altmetrics

docs.bsky.app

Action Intent Links | Bluesky

Authors, websites, and apps can use action intent links to implement "Share on Bluesky" buttons, or similar in-app actions. Logged-in users will be directed to the corresponding action view in the Blu...

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Mridul K. Thomas @mridulkthomas.bsky.social · 18/11/2024

This predated the X-odus, so I thought I'd bump it. #rstats brms is a fantastic tool that has made it so much easier to work with Bayesian models. And to teach - I'm going to introduce my stats students to the concepts this week and have them dive right in and start fitting models.

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Maarten van Smeden @maartenvsmeden.bsky.social · 18/11/2024

I made one for stats papers

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Hadley Wickham @hadley.nz · 17/11/2024

I'd love to include a bunch of examples of what you can use LLMs for in the elmer documentation to inspire #rstats developers? What cool tools have you used or created? (Bonus points if they have public R code I can link to).

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Marvin Schmitt @marvin-schmitt.com · 17/11/2024

I created a starter pack of scientists in the European Laboratory for Learning and Intelligent Systems (ELLIS) 🇪🇺 Please ping me and I‘ll add you. go.bsky.app/Cihupkk

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Mr. Chau @srirachachau.bsky.social · 16/11/2024

Seeing all my old friends on here again

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Anne Oeldorf-Hirsch @anneo.bsky.social · 16/11/2024

When I came here to 🦋 last year it was a ghost town for so long. Now it finally feels like maybe I have an online #AcademicSky network to chat with again! I’m just realizing how much of a hole leaving that on X left in my life.

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Paul Bürkner @paulbuerkner.com · 16/11/2024

It feels that the longer I do statistics, the harder it becomes. I never get an analysis just "right". There is always one more assumption to change or one more term to add to my model.

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Vincent Arel-Bundock @vincentab.bsky.social · 15/11/2024

FWIW, I've recently spent a ton of time working to improve `tinyplot` with Grant and Achim. The upcoming version is going to be amazing. Ultra-concise syntax for all the common plots, with auto legend, groups, and facets. 0-dep. For interactive use and teaching, this is going to be great.

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Paul Bürkner @paulbuerkner.com · 14/11/2024

I am not usually a fan boy of anything, but I must say the new Linkin Park album makes me feel weirdly excited! A lot of good teenage memories come to mind.

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Isabella Velásquez @ivelasq3.bsky.social · 01/11/2024

Want to add a Bluesky icon to your #Quarto site? 🦋 • Install quarto-iconify: github.com/mcanouil/qua... • Add as 'text' - text: "{{< iconify simple-icons bluesky >}}" href: bsky.app/profile/ivel... Example code: github.com/ivelasq/pipe... Related GH link: github.com/quarto-dev/q...

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Olivier Simard-Casanova @o.simardcasanova.net · 01/11/2024

I don’t care if you have many followers or (still) get a lot of engagement on Xitter In today’s age, continuing to post content to this rotten platform is helping legitimizing a massive and brutal attack against democracy itself It’s time to leave Many of us did, and we turned out more than fine

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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 01/11/2024

tags for the tag god! #stats 🧪

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