juanitorduz
juanitorduz.bsky.social
juanitorduz
@juanitorduz.bsky.social
Applied Scientist | Math PhD | Open Source
PyMC Labs
https://juanitorduz.github.io
Reposted by juanitorduz
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
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.
ropensci.org
February 5, 2025 at 3:40 PM
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).
October 14, 2025 at 12:22 PM
Reposted by juanitorduz
7 reasons to use Bayesian inference!
statmodeling.stat.columbia.edu/2025/10/11/7...
7 reasons to use Bayesian inference! | Statistical Modeling, Causal Inference, and Social Science
statmodeling.stat.columbia.edu
October 11, 2025 at 1:54 PM
It was fun (painful 😅) to implement VAR(p) models from scratch juanitorduz.github.io/var_numpyro/
Bayesian Vector Autoregressive Models in NumPyro - Dr. Juan Camilo Orduz
juanitorduz.github.io
October 3, 2025 at 6:22 PM
Festival der Riesendrachen
#Berlin
September 27, 2025 at 5:59 PM
Reposted by juanitorduz
Reproducing Uber's Alternating Direction Method of Multipliers (ADMM) based automated budget allocation system in JAX

gstechschulte.github.io/posts/2025-0...
Reproducing Uber's Marketplace Optimization
Uber allocates money across different regions and programs to incentivize riders and drivers to use Uber products. This incentive structure ultimately influences the market. This leads to the natural ...
gstechschulte.github.io
September 25, 2025 at 12:44 PM
Reposted by juanitorduz
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 📊
September 18, 2025 at 2:38 PM
Reposted by juanitorduz
A nice primer on normalizing flows by PyMC/PyTensor devs Ricardo and Jesse. pytensor.readthedocs.io/en/latest/ga...
Normalizing Flows in PyTensor — PyTensor dev documentation
pytensor.readthedocs.io
September 15, 2025 at 8:39 PM
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/
Scaling Probabilistic Models with Variational Inference
juanitorduz.github.io
September 13, 2025 at 8:02 AM
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 🫶
LinkedIn
This link will take you to a page that’s not on LinkedIn
lnkd.in
July 9, 2025 at 5:29 PM
Los Amigos Invisibles #Berlin
July 6, 2025 at 9:56 PM
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
July 1, 2025 at 7:12 PM
I used to experience this and it is fucking horrible 🫠
cnn.com CNN @cnn.com · Jun 8
An estimated 30% of people worldwide experience at least one episode of sleep paralysis in their lifetime, according to the Cleveland Clinic.

Here’s what you should know about sleep paralysis and how it can be managed.
The science of sleep paralysis, a brain-body glitch making people see demons and witches | CNN
Around 30% of people will experience sleep paralysis at least once. Here’s why and what you can do about it.
www.cnn.com
June 8, 2025 at 8:22 PM
May 17, 2025 at 8:46 PM
Reposted by juanitorduz
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...
Probabilistic Time Series Analysis: Opportunities and Applications - PyMC Labs
dub.sh
April 30, 2025 at 5:23 PM
Reposted by juanitorduz
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
April 29, 2025 at 6:14 PM
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...
Introduction to Bayesian Power Analysis: Exclude a Null Value - Dr. Juan Camilo Orduz
juanitorduz.github.io
April 29, 2025 at 1:29 PM
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...
Probabilistic Time Series Analysis: Opportunities and Applications - PyMC Labs
www.pymc-labs.com
April 28, 2025 at 12:47 PM
I decided to wrap these cohort modeling techniques in a little pre-print 🤗

arxiv.org/abs/2504.16216
Cohort Revenue & Retention Analysis: A Bayesian Approach
We present a Bayesian approach to model cohort-level retention rates and revenue over time. We use Bayesian additive regression trees (BART) to model the retention component which we couple with a lin...
arxiv.org
April 25, 2025 at 12:14 PM
Reposted by juanitorduz
Time Series Analysis with StatsModels

Video from my PyData Global tutorial is up now:
www.youtube.com/watch?v=foMb...
Allen Downey - Time Series Analysis with StatsModels | PyData Global 2024
YouTube video by PyData
www.youtube.com
April 24, 2025 at 2:11 PM
Reposted by juanitorduz
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
Forecasting: Principles and Practice, the Pythonic Way
otexts.com
April 11, 2025 at 12:25 AM
Reposted by juanitorduz
📚😅🎉

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
April 10, 2025 at 7:06 PM
This is my current readingI had it in my mind for many years and I finally decided to read it! So far so good!
April 8, 2025 at 7:18 PM
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...
Vienna Workshop on Economic Forecasting 2020
The submission deadline for the 2nd Vienna Workshop on Economic Forecasting has been extended to August 31st.
www.ihs.ac.at
March 29, 2025 at 12:02 PM
Reposted by juanitorduz
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...
Synthetic Consumers: The Promise, The Reality, and The Future - PyMC Labs
www.pymc-labs.com
March 26, 2025 at 5:13 PM