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Eleonora Giunchiglia

@e-giunchiglia.bsky.social did:plc:vljimyetuh2ye24cnyvx2uuy

Assistant Professor at Imperial College London | EEE Department and I-X. Neuro-symbolic AI, Safe AI, Generative Models Previously: Post-doc at TU Wien, DPhil at the University of Oxford.

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Résumé

Eleonora Giunchiglia (@e-giunchiglia.bsky.social) est sur Bluesky depuis le 21 novembre 2024. Le compte a 736 abonnés, suit 268 comptes et a publié 38 posts.

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  • Tim Green@otherprofgreen.bsky.social

    I’ve been down to Rye on the train, mainly to not just spend a day in the house. It was cold at first but has turned out nice. Walked from Rye to Rye Harbour and on to the coast, which has move a lot over the centuries. Of course, it also needed defences against Napoleon and Hitler.

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  • Adrián Javaloy@javaloyml.bsky.social

    It has been a while since I have been active here, and lots of things have changed: different city, different role. I have been swamped, but I finally managed to update my website. More news sooner than later! (I accept suggestions for lab names) adrianjav.github.io

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  • vincenzocollura.bsky.social@vincenzocollura.bsky.social

    𝐋𝐋𝐌: “Don’t worry, I’m following the grammar.” 𝐀𝐥𝐬𝐨 𝐋𝐋𝐌: [incomplete output] … [invalid syntax] Happy to share that our paper “𝐒𝐭𝐚𝐲 𝐖𝐢𝐭𝐡𝐢𝐧 𝐘𝐨𝐮𝐫 𝐁𝐨𝐮𝐧𝐝𝐬: 𝐃𝐢𝐬𝐭𝐚𝐧𝐜𝐞-𝐆𝐮𝐢𝐝𝐞𝐝 𝐃𝐞𝐜𝐨𝐝𝐢𝐧𝐠 𝐟𝐨𝐫 𝐆𝐮𝐚𝐫𝐚𝐧𝐭𝐞𝐞𝐝 𝐂𝐨𝐧𝐭𝐞𝐱𝐭-𝐅𝐫𝐞𝐞 𝐆𝐫𝐚𝐦𝐦𝐚𝐫 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞” has been accepted to the 𝐅𝐢𝐧𝐝𝐢𝐧𝐠𝐬 𝐨𝐟 𝐄𝐌𝐍𝐋𝐏 𝟐𝟎𝟐𝟔!

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  • Emile van Krieken@emilevankrieken.com

    Almost off to @euripsconf.bsky.social in Copenhagen 🇩🇰 🇪🇺! I'll present 3 posters: 🧠 Neurosymbolic Diffusion Models: Thursday's poster session. Going to NeurIPS? @edoardo-ponti.bsky.social and @nolovedeeplearning.bsky.social will present the paper in San Diego Thu 13:00 arxiv.org/abs/2505.13138

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  • Samy Badreddine@sbadredd.bsky.social

    Emile will present our work on Knowledge Graph Embeddings at Eurips' Salon des Refusés on Friday! We show how linearity prevent KGEs from scaling to larger graphs + propose a simple solution using a Mixture of Softmaxes (see LLM literature) to break the limitations at a low parameter cost. 🔨

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