iiinova — where your digital self keeps evolving

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Terence Tao @teorth.bsky.social · 11/09/2026

A group of 25 Fields Medalists, including myself, have made a joint declaration on Math and AI: mathandai.org . We welcome additional signatories. See also this article in the Economist announcing the declaration: www.economist.com/science-and-...

mathandai.org

Declaration — Math and AI

Read the declaration and add your name.

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PyMC Labs @pymc-labs.bsky.social · 07/09/2026

Happening TOMORROW at 11:00 AM ET! Turn slow MCMC sampling into sub-second forward passes using Generative AI (BayesFlow + PyMC). Join Stefan Radev, Thomas Wiecki, & Luca Fiaschi live to ask questions & get the full recording + code: dub.sh/9Jx1fii #PyMC #GenAI

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PyMC Labs @pymc-labs.bsky.social · 10/08/2026

PyMC-Marketing v1.0 is live! Stable Bayesian marketing analytics by PyMC Labs: • Multidimensional & ~1.5x faster • Predicted Incrementality (PIE) • Funnel-Aware MMM • Long-Term Brand Effects Docs & Release: dub.sh/NIB4SZm #MMM #PyMC

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juanitorduz @juanitorduz.bsky.social · 27/06/2026

I want to share a very raw project, “NumPyro Forecast”. It is based on Pyro’s forecasting module docs.pyro.ai/en/dev/contr... (an actual port to Jax and NumPyro). I plan to extract many of the custom models I have from my blog and other places :) github.com/juanitorduz/...

github.com

GitHub - juanitorduz/numpyro_forecast: Forecasting Models in NumPyro

Forecasting Models in NumPyro. Contribute to juanitorduz/numpyro_forecast development by creating an account on GitHub.

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juanitorduz @juanitorduz.bsky.social · 24/04/2026

Since more than 3 months I haven’t used Bluesky much…I am not finding stats Twitter from 2021 😔. I might just close the account and safe some phone battery …

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Barbara Fantechi @barbarafantechi.bsky.social · 06/04/2026

Absolutely heartbreaking. So many mathematicians I know studied there, men AND women. Maryam Mirzakhani studied there. If this isn't enough to cancel/relocate from the US the International Congress of Mathematicians #ICM2026, nothing will be.

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ArviZ @arviz.bsky.social · 01/04/2026

ArviZ 1.0 brings a lot of new plotting functionality. Check our gallery for a glimpse of what's new: python.arviz.org/projects/plo...

python.arviz.org

Example gallery — arviz-plots dev documentation

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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 22/03/2026

Statistical Rethinking 2026 is done: 20 new lectures emphasizing logical and critical statistical workflow, from basics of probability theory to causal inference to reliable computation to sensitivity. It's all free, made just for you. Lecture list and links: github.com/rmcelreath/s...

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juanitorduz @juanitorduz.bsky.social · 28/03/2026

@rmcelreath.bsky.social I followed all the B course of statistical rethinking 2026. It was amazing! Thank you much for sharing! (I’m said it is over 🥲)

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PyMC Labs @pymc-labs.bsky.social · 25/03/2026

An MMM can predict perfectly, and still get causality wrong. This chart shows it: uncalibrated ROAS posteriors miss reality. Add one lift test → estimates snap back to truth. Join our MMM Calibration deep dive Webinar (Apr 8): dub.link/Nax7e44

PyMC-Marketing ROAS Posterior Distribution

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ArviZ @arviz.bsky.social · 19/03/2026

ArviZ 1.0 is out! We have refactored it to be more modular, flexible & lightweight. For an overview of the changes, check the migration guide. python.arviz.org/en/stable/us...

python.arviz.org

Getting started — ArviZ 1.0.0 documentation

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juanitorduz @juanitorduz.bsky.social · 01/01/2026

I am super excited to join @pymc-labs.bsky.social full-time! I will be working on open-source projects, helping companies leverage Bayesian methods for decision-making, developing tailored educational workshops for industry practitioners, and serving as a product manager for our AI products.

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juanitorduz @juanitorduz.bsky.social · 29/11/2025

Here are two examples on causal inference and through the lens of probabilistic programming languages (PPLs): - Introduction to Causal Inference with PPLs juanitorduz.github.io/intro_causal... - Causal Inference with Multilevel Models: juanitorduz.github.io/ci_multilevel/ Implementations in PyMC.

lnkd.in

This link will take you to a page that’s not on LinkedIn

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juanitorduz @juanitorduz.bsky.social · 23/11/2025

Here is the recording of my talk PyData Berlin 2025: Introduction to Stochastic Variational Inference with NumPyro Notebook: juanitorduz.github.io/intro_svi/ youtu.be/wG0no-mUMf0?... #pydata #berlin #bayes

youtu.be

Scaling Probabilistic Models with Variational Inference

YouTube video by PyData

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Noam Ross @noamross.net · 05/02/2025

Open Science and Open Source only with Diversity, Equity, Inclusion and Accessibility. Inclusion is essential to science, and science is only worthwhile if it lifts everyone up together. ropensci.org/blog/2025/02... #OpenSource #OpenScience

ropensci.org

Open Science and Open Source only with Diversity, Equity, Inclusion, and Accessibility

Including all of humanity is and always will be at the heart of open science.

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juanitorduz @juanitorduz.bsky.social · 14/10/2025

I got mail! I can’t not wait @vincentab.bsky.social I’ll try to do many of these examples by “hand” (learning by doing).

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juanitorduz @juanitorduz.bsky.social · 03/10/2025

It was fun (painful 😅) to implement VAR(p) models from scratch juanitorduz.github.io/var_numpyro/

juanitorduz.github.io

Bayesian Vector Autoregressive Models in NumPyro - Dr. Juan Camilo Orduz

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Jan Boelts @janboelts.bsky.social · 18/09/2025

Kudos to @sethaxen.com for implementing the Pyro wrapper that makes this possible (shipped in sbi v0.25)! And thanks to @juanitorduz.bsky.social sharing the cookie factory example—it's a great accessible example for hierarchical inference. Everything runs in Colab 📊

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Chris Fonnesbeck @fonnesbeck.bsky.social · 15/09/2025

A nice primer on normalizing flows by PyMC/PyTensor devs Ricardo and Jesse. pytensor.readthedocs.io/en/latest/ga...

pytensor.readthedocs.io

Normalizing Flows in PyTensor — PyTensor dev documentation

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juanitorduz @juanitorduz.bsky.social · 13/09/2025

Here are the materials for the PyData Berlin 2025 talk on Stochastic Variational Inference with NumPyro: - Slides: juanitorduz.github.io/html/intro_s... - Notebook; juanitorduz.github.io/intro_svi/

juanitorduz.github.io

Scaling Probabilistic Models with Variational Inference

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juanitorduz @juanitorduz.bsky.social · 09/07/2025

The ArviZ core devs have done tremendous work on an improved API with a lot of novel improvements. They have put together a great migration guide: python.arviz.org/en/stable/us... If you are an ArviZ user please take a look at it and provide feedback. Open source is all about the community 🫶

lnkd.in

This link will take you to a page that’s not on LinkedIn

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juanitorduz @juanitorduz.bsky.social · 01/07/2025

I’ll be giving a talk ok variational inference (VI) at PyData Berlin 2025 🙂! I’ll focus on some learnings of using VI for forecasting models at scale. If you are around come and say hi. #PyDataBerlin

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juanitorduz @juanitorduz.bsky.social · 08/06/2025

I used to experience this and it is fucking horrible 🫠

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PyMC Labs @pymc-labs.bsky.social · 30/04/2025

Forecasting isn’t just about prediction — it’s about decision-making under uncertainty. @juanitorduz.bsky.social shows how Bayesian models help: 🔹 Sparse data? Use hierarchies 🔹 Stockouts? Use censored likelihoods 🔹 Messy demand? Use priors + state spaces Practical guide 👉 dub.sh/prob-forecas...

dub.sh

Probabilistic Time Series Analysis: Opportunities and Applications - PyMC Labs

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Ursula von der Leyen @vonderleyen.ec.europa.eu · 29/04/2025

Freedom of science and research is one of Europe's great strengths. It’s how excellence and innovation thrive. We’ll make proposals to help scientists and researchers ‘Choose Europe’. The best and brightest from around the world.   To make Europe the home of innovation again. → europa.eu/!JFF7jm

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juanitorduz @juanitorduz.bsky.social · 29/04/2025

Here is a first intro notebook on Bayesian Power Analysis following the method described in the paper "The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective" (link.springer.com/content/pdf/...) juanitorduz.github.io/power_sample...

juanitorduz.github.io

Introduction to Bayesian Power Analysis: Exclude a Null Value - Dr. Juan Camilo Orduz

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juanitorduz @juanitorduz.bsky.social · 28/04/2025

Here is a new blog post with PyMC Labs: "Probabilistic Time Series Analysis: Opportunities and Applications." We provide a collection of business cases where probabilistic methods excel in real-world applications of probabilistic time series methods. www.pymc-labs.com/blog-posts/p...

pymc-labs.com

Probabilistic Time Series Analysis: Opportunities and Applications - PyMC Labs

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Allen Downey @allendowney.bsky.social · 24/04/2025

Time Series Analysis with StatsModels Video from my PyData Global tutorial is up now: www.youtube.com/watch?v=foMb...

youtube.com

Allen Downey - Time Series Analysis with StatsModels | PyData Global 2024

YouTube video by PyData

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Rob Hyndman @robjhyndman.com · 11/04/2025

A new Python edition of "Forecasting: Principles and Practice" is now available online at otexts.com/fpppy/. Thanks to @azulgarza.bsky.social, Cristian Challu, Max Mergenthaler, Kin Olivares & Nixtla for making this happen. #forecasting #python

otexts.com

Forecasting: Principles and Practice, the Pythonic Way

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Vincent Arel-Bundock @vincentab.bsky.social · 10/04/2025

📚😅🎉 Yay!! I just submitted the complete manuscript of my upcoming book to the publisher! Learn to easily and clearly interpret (almost) any stats model w/ R or Python. Simple ideas, consistent workflow, powerful tools, detailed case studies. Read it for free @ marginaleffects.com #RStats #PyData

Model to Meaning: How to interpret statistical models with marginaleffects for R and Python

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juanitorduz @juanitorduz.bsky.social · 08/04/2025

This is my current readingI had it in my mind for many years and I finally decided to read it! So far so good!

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juanitorduz @juanitorduz.bsky.social · 29/03/2025

I’ll be attending the 3rd Vienna Workshop on Economic Forecasting 2025 where I will have a poster on “Probabilistic Forecasting at Scale with NumPyro” 🙂 www.ihs.ac.at/current/even...

ihs.ac.at

Vienna Workshop on Economic Forecasting 2020

The submission deadline for the 2nd Vienna Workshop on Economic Forecasting has been extended to August 31st.

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Allen Downey @allendowney.bsky.social · 26/03/2025

At PyMC Labs I've been working with a group developing synthetic consumers for marketing research. We just published this white paper with an overview of work in this space -- and we have a blog post coming next week with some experimental results. www.pymc-labs.com/blog-posts/s...

pymc-labs.com

Synthetic Consumers: The Promise, The Reality, and The Future - PyMC Labs

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PyMC Labs @pymc-labs.bsky.social · 26/03/2025

We just launched our first white paper! By 2027, AI-generated consumers could power 50%+ of market research data. 📄 What’s inside? ✅ What synthetic consumers are ✅ How businesses use them and more.... 🔗 dub.sh/61AEavU 📩 Curious how this could benefit your org? 👉 info@pymc-labs.com #GenAI

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juanitorduz @juanitorduz.bsky.social · 23/03/2025

We just released PyMC-Marketing with a new multidimensional MMM class to allow for custom hierarchical model across multiple dimensions (e.g. geographies). You can specify hierarchical components easily so the opportunities are huge. www.pymc-marketing.io/en/stable/no... #mmm #pymc #marketing

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 22/03/2025

Open source is draining. One's todo-list is open to world. People seldom realize the cost of what they get for free. Unpleasant comments do happen. Cost of maintenance is not understood. opensource.com/article/17/2...

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Demetri @phdemetri.bsky.social · 18/03/2025

It was suggested by @juanitorduz.bsky.social that I add some simulation proof to some claims I make in my blog post over at geteppo.com By all means, have some simulation proof (plus a little explanation of what I said re: pulling estimates apart) dpananos.github.io/posts/2025-0...

dpananos.github.io

Demetri Pananos Ph.D - More on Bayesian Statistics

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 10/03/2025

🔥🎉New library: boosting for survival analysis, including multiclass (competing risks) Survival = missing outcomes because limited observation window (common in medicine, marketting...) soda-inria.github.io/hazardous Gives very fast boosted-trees for survival

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Aki Vehtari @avehtari.bsky.social · 06/03/2025

My favorites: Challenges and opportunities... proceedings.neurips.cc/paper/2021/h... Robust, accurate stochastic optimization... papers.nips.cc/paper/2020/h... ...improving the reliability of black-box VI jmlr.org/papers/v25/2... Yes, but Did It Work? ... proceedings.mlr.press/v80/yao18a.h...

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juanitorduz @juanitorduz.bsky.social · 05/03/2025

Hi! Here is a question for all the #bayesian folks! Can you recommend references on evaluation and diagnostics of (stochastic) variational inference? Anything would be much appreciated 🙏

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Peter Tennant @pwgtennant.bsky.social · 13/01/2025

"Have directed acyclic graphs fullfilled their promise?" - the recording of my debate with @margaritamb.bsky.social at the World Congress of Epidemiology 2024 is now available on YouTube! www.youtube.com/watch?v=FG79... #EpiSky #CausalSky #WCE2025

youtube.com

WCE2024 - INT02 - Debate - Have DAGS fulfilled their promise?

YouTube video by World Congress of Epidemiology 2024

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PyMC Labs @pymc-labs.bsky.social · 04/03/2025

𝐏𝐲𝐌𝐂-𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐢𝐬 𝐠𝐫𝐨𝐰𝐢𝐧𝐠 𝐟𝐚𝐬𝐭. We’ve crossed 175,000 𝐭𝐨𝐭𝐚𝐥 𝐝𝐨𝐰𝐧𝐥𝐨𝐚𝐝𝐬 & now hit 20,000 𝐦𝐨𝐧𝐭𝐡𝐥𝐲 𝐝𝐨𝐰𝐧𝐥𝐨𝐚𝐝𝐬. 🤔𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐨𝐟 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐈𝐧-𝐇𝐨𝐮𝐬𝐞? Developing a custom solution can take 𝐦𝐨𝐧𝐭𝐡𝐬, 𝐏𝐲𝐌𝐂-𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 gets you there 𝐟𝐚𝐬𝐭𝐞𝐫 📅 𝐒𝐜𝐡𝐞𝐝𝐮𝐥𝐞 𝐚 𝐅𝐫𝐞𝐞 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐭𝐢𝐨𝐧 : calendly.com/niall-oulton

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