Today we have @lennertds.bsky.social from KU Leuven teaching us how to adapt NeSy methods to deal with sequential problems 🚀

Super interesting topic combining DL + NeSy + HMMs! Keep an eye on Lennert's future works!

This year I am co-organizing the 8th iteration of the Tractable Probabilistic Modeling #TPM workshop at #UAI2025 🌴 Rio de Janeiro edition 🌴

🌐 lnkd.in/dDK8T5Au
⏰ Submission deadline: May 23th AoE
🌴 Date: July 15th

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Why doing that when you could go full bash tho?

Apologies too! 👒

For refs: superuser.com/questions/15...

If you prefer to read a practical example, you can find a basic tutorial here: causal-flows.readthedocs.io/en/latest/tu...

Using a triangular SCM as an example (x1 -> x2, x3 and x2 -> x3), I show how to fit a Causal NF on observational data (left), and use it for causal inference (right).

With this new library, defining and training a Causal NF can be as simple as using any other predefined NF.

If you feel fancy, you can also build your own Causal NF composing any transformation and distribution from the Zuko library for regular NFs (github.com/probabilists...) 👷

👏 every 👏 single 👏 damn 👏 time 👏

Note to self: why do I even keep trying it?

Thanks for sharing Alex! It looks super interesting

Also, wow... 🫠

Over the years, I have developed this bad habit of typing twitter on the address bar when I don't know what to do, which made me never really quit it.

This time, I am redirecting that habit somewhere else 🙄

PS: The add-on is called Redirector: addons.mozilla.org/en-GB/firefo...