New preprint out! Networks of Causal Abstractions: A Sheaf-theoretic Framework arxiv.org/abs/2509.25236

3 x ✅ causal abstraction: arxiv.org/abs/2602.026... functorial signal processing: arxiv.org/abs/2510.112... probabilistic topological modeling: arxiv.org/abs/2510.129... #ICASSP2026

📢New publication in the Proc. of the 59th Asilomar Conference on semantic alignment and communication of AI agents using network sheaves! 🤖 arxiv.org/pdf/2512.03248

New publication in the Proc. of the 59th Asilomar Conference from the SPAICOM Lab for probabilistic modeling over higher-order topological domains arxiv.org/pdf/2512.03727

Ready to fly to Vancouver 🛸 Eager to talk about causal abstraction at @icmlconf.bsky.social #icml2025 #causal #ML

📢"The Relativity of #Causal Knowledge" has been accepted at the 41st edition of the Conference on #Uncertainty in #AI. Thanks to @clabat9.bsky.social for his essential contribution and commitment. Camera-ready coming soon 👽 #uai2025 #ML

#ICML 2025 here we come! **Causal Abstraction Learning based on the Semantic Embedding Principle** Stay tuned for the camera-ready version (spoiler: new results are on the way!) Fabio Massimo Zennaro, @yfelekis.bsky.social and Paolo Di Lorenzo #causal #ML

📢📢📢"The Relativity of Causal Knowledge" THANK YOU to @clabat9.bsky.social for working side by side with me on this exciting project and making this article possible. Big thanks also to @hansmriess.bsky.social and Fabio Massimo Zennaro for their valuable feedback on an earlier version of the paper.

Hot off the press!💥 arxiv.org/abs/2502.00407