and to @leanderk.bsky.social @paolomorettin.bsky.social Roberto Sebastiani, @andreapasserini.bsky.social @nolovedeeplearning.bsky.social for the ✨Best Student Paper Runner Up Award✨ for "A Probabilistic Neurosymbolic Layer for Algebraic Constraint Satisfaction" 👉 openreview.net/forum?id=9Uk...

24 hours more to submit your latest papers on #TPMs!

We propose Neurosymbolic Diffusion Models! We find diffusion is especially compelling for neurosymbolic approaches, combining powerful multimodal understanding with symbolic reasoning 🚀 Read more 👇

🚨 New paper: “Towards Adaptive Self-Normalized IS”, @ IEEE Statistical Signal Processing Workshop. TLDR; To estimate µ = E_p[f(θ)] with SNIS, instead of doing MCMC on p(θ) or learning a parametric q(θ), we try MCMC directly on p(θ)| f(θ)-µ | (variance-minimizing proposal). arxiv.org/abs/2505.00372

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!

It’s great to have @wouterboomsma.bsky.social talking at UoE today! Happening at 2pm at EFI 2.35.

the #TPM ⚡Tractable Probabilistic Modeling ⚡Workshop is back at @auai.org #UAI2025! Submit your works on: - fast and #reliable inference - #circuits and #tensor #networks - normalizing #flows - scaling #NeSy #AI ...& more! 🕓 deadline: 23/05/25 👉 tractable-probabilistic-modeling.github.io/tpm2025/

I am at @realaaai.bsky.social #AAAI25 in sunny #Philadelphia 🌞 reach out if you want to grab coffee and chat about #probabilistic #ML #AI #nesy #neurosymbolic #tensor #lowrank models! check out our tutorial 👉 april-tools.github.io/aaai25-tf-pc... and workshop 👉 april-tools.github.io/colorai/

Have you ever been curious to try Causal Normalizing Flows for your project but found them intimidating? Say no more 😜 I just released a small library to easily implement and use causal-flows: github.com/adrianjav/ca...

Interested in estimating posterior predictives in Bayesian inference? Really want to know if your approximate inference "is working"? Come to our poster at the NeurIPS BDU workshop on Saturday - see TL;DR below.

many of the recent successes in #AI #ML are due to #structured low-rank representations! but...What's the connection between #lowrank adapters, #tensor networks, #polynomials and #circuits? join our #AAAI25 workshop to know the answer! and 2 more days to submit! 👇👇👇 april-tools.github.io/colorai/