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Reposted by Lena Zellinger

antonio vergari ⚔️ short-circuiting @nolovedeeplearning.bsky.social · 02/06/2025

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

Reposted by Lena Zellinger

Emile van Krieken @emilevankrieken.com · 21/05/2025

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

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Reposted by Lena Zellinger

Nicola Branchini @nicolabranchini.bsky.social · 02/05/2025

🚨 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

arxiv.org

Towards Adaptive Self-Normalized Importance Samplers

The self-normalized importance sampling (SNIS) estimator is a Monte Carlo estimator widely used to approximate expectations in statistical signal processing and machine learning. The efficiency of S...

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Reposted by Lena Zellinger

Adrián Javaloy @javaloyml.bsky.social · 30/04/2025

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!

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Lena Zellinger @lenazellinger.bsky.social · 28/04/2025

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

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Reposted by Lena Zellinger

antonio vergari ⚔️ short-circuiting @nolovedeeplearning.bsky.social · 16/04/2025

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/

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Reposted by Lena Zellinger

antonio vergari ⚔️ short-circuiting @nolovedeeplearning.bsky.social · 25/02/2025

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/

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Reposted by Lena Zellinger

Adrián Javaloy @javaloyml.bsky.social · 13/02/2025

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...

github.com

GitHub - adrianjav/causal-flows: CausalFlows: A library for Causal Normalizing Flows in Pytorch

CausalFlows: A library for Causal Normalizing Flows in Pytorch - adrianjav/causal-flows

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Reposted by Lena Zellinger

Nicola Branchini @nicolabranchini.bsky.social · 11/12/2024

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.

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Reposted by Lena Zellinger

antonio vergari ⚔️ short-circuiting @nolovedeeplearning.bsky.social · 21/11/2024

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/

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