Veronica Lachi
@LachiVeronica
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PhD student, University of Siena 🇮🇹 Visiting PhD student, University of Tromsø 🇳🇴 GNN, GDL
Sienna, Tuscany
Joined April 2021
🚀 How much can Network Science boost AI? And vice versa? 🤔 Join HONS meets AI workshop at #NetSci2025 to explore these questions! 📢 Submit your work & be part of the discussion! https://t.co/O3Jc59PupD with @alessiaantelmi @ManuelDileo @VincentPGrande @yllka_velaj @vins23p
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Gentle reminder for those interested in the Italian @LogConference meetup: submissions close at the end of this week! 📅 Submit your abstract here:
sites.google.com
Call for Posters The meetup will host a local poster session (independent from the main event). We welcome posters from areas broadly related to learning on graphs and geometry. Poster abstracts must...
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🤔 How to interpret spatio-temporal data and deep learning models? 💡In our recent work with Michele Guerra and @s_scardapane we leverage Koopman theory to design an XAI framework for spatio-temporal GNNs. 📄 Preprint: https://t.co/cThmDCIgqM 💻 Code: https://t.co/N74aF8bCT8
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📢Exciting news, graph folks! Registrations for the Italian meetup of the @LogConference are now OPEN!😱✨️ 👉🏽 Secure your spot and register here! https://t.co/j1zR7HLa2z
#LoG #siena #meetup #registration
sites.google.com
Learning on Graphs is an annual research conference that covers areas broadly related to machine learning on graphs and geometry. Siena will host the 2024 Italy meetup. 🗓️ 4-6 December 2024 📍...
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We are glad to announce that the @LogConference Italian meet-up will be hosted in Siena! 🇮🇹✨️ 🗓️ Join us from December 4th to 6th. 🔜 Registration will open soon! 👉 For more information visit our website : https://t.co/bN7ehxSpJ2
#log #graphs #graphlearning #ml #siena #gnn
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🧵 Ready for #ICML2024! This year me and @FilippoMariaBi1 present a method to forecast correlated time series with missing data. We compute a hierarchy of multi-scale spatiotemporal representations and adaptively combine them conditioned on the missing data pattern👇
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🚀Interested in link prediction? Discover how a simple GNN can learn structural link representation! 📜A Simple and Expressive GNN Method for Structural Link Representation @LachiVeronica will present it at @GRaM_workshop (@icmlconf) @franciferrini_ @brulepri @andrea_whatever
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🚨Today is the turn of Veronica Lachi! @LachiVeronica 👀Veronica is a Researcher working on Graph Neural Networks, with a special interest in their theoretical properties. She is particularly interested in the expressiveness of GNNs and GNNs for temporal graphs.
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Join our exclusive AI4BA Summer School and catch the opportunity to live a study-week immersed in the Tuscanian hills! AI for Biomedical Applications 🕒24-28 June 2024 📍Siena Only 14 spots available! Visit the AI4BA site! 👉🏽 https://t.co/oaem8kN0hC And submit your application!
sites.google.com
Photo by Franco Scarselli
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🌟 Join us this week, thursday Feb 29th, 11am EST, as Veronica Lachi @LachiVeronica presents "Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities". Don't miss out! 🚀 [Link: https://t.co/Ycba8SILUG]
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To the @NeurIPSConf Folks! Can path-aggregation increase the expressive power of GNNs? Come visit our poster at #GLFrontiers to find this out (and to appreciate the creativity of @geneticpizza)! 11.30 in HALL C2 ;) #NeurIPS2023 #GLFrontiers
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Join us at the #NeurIPS2023 poster session this afternoon where @LachiVeronica and I will present the poster of our paper, "The Expressive Power of Pooling in Graph Neural Networks". See you at poster #822 from 5:00 PM to 7:00 PM
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First evening in New Orleans at #NeurIPS 2023 with @andreacini1994, @LachiVeronica, @dan_zambon, @IvanMarisca and many more awesome colleagues!
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Hey NetPALS, have you ever wondered what Graph Neural Networks (GNNs) are? In our last seminar, @LachiVeronica from the University of Siena covered this topic extensively in her talk “Machine Learning for Graphs: Hot Trends and Emerging Frontiers”.[1/4]
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🚀Exciting news! "The Expressive Power of Pooling in Graph Neural Networks" by @FilippoMariaBi1 and me, has been accepted at @NeurIPSConf and it's been chosen as one of the top 4 papers for an oral presentation at #mlg workshop during @ECMLPKDD! #NeurIPS2023 #GNN 📚 💻
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Attended a captivating session at the #MLG workshop during @ECMLPKDD, exploring "The Expressive Power of Pooling in Graph Neural Networks" authored by @FilippoMariaBi1 & presented by @LachiVeronica. paper: https://t.co/QlNKpfwaqU
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Exciting news for all #GraphEnthusiasts! Join us in Trento from Nov 27-30 for a local meetup of the #LoG Conference. Connect with researchers, stay updated on the latest in graph learning, and foster collaboration. Register by Nov 19! Learn more at
eventbrite.it
Italy meetup of the Learning on Graph Conference, an annual research event in machine learning on graphs and geometry 27th – 30th November
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Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities Antonio Longa, Veronica Lachi, Gabriele Santin et al.. Action editor: Shinichi Nakajima. https://t.co/bIvHRByGCw
#temporal #graphs #graph
openreview.net
Graph Neural Networks (GNNs) have become the leading paradigm for learning on (static) graph-structured data. However, many real-world systems are dynamic in nature, since the graph and node/edge...
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📢 New preprint out! Introducing HiGP, a framework unifying graph pooling with hierarchical time series forecasting. Our end-to-end approach allows for clustering and forecasting time series at multiple levels of aggregation. Check it out: https://t.co/XXUMa21vQR
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