Andrea Cini
@andreacini1994
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🇨🇭/🇬🇧 SNSF Postdoc Fellow at @UniofOxford. Postdoc affiliate @UiTNorgesarktis 🇳🇴 and @USI_university 🇨🇭 - Time series and graphs
Joined July 2017
Big personal update 😊. I'm moving to @UniofOxford to work with @mmbronstein on my recently funded Swiss National Science Foundation project 🎉🎉. As part of the project, I'll also be collaborating with @FilippoMariaBi1 😃. Looking forward to exciting new research & collabs! 😎.
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Closing out August in the Arctic, cooking up cool new research with @FilippoMariaBi1 and @beertorob! . Stay tuned 👀🏔️
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RT @tgl_workshop: Join the Temporal Graph Learning Workshop at KDD 2025, we have an amazing program with great speakers and papers waiting….
sites.google.com
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RT @jacobbamberger: 🚨 ICML 2025 Paper 🚨. "On Measuring Long-Range Interactions in Graph Neural Networks". We formalize the long-range probl….
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I will be in Vancouver next week for #ICML2025! If you’re around, would love to catch up 😊 . Also, if you’re interested in uncertainty quantification in time series forecasting, come say hi at poster E-1706 on Tuesday from 16:30 to 19:00!
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Freshly accepted as a tutorial paper in ACM Computing Surveys! 🥳. Check out the updated version: cc @IvanMarisca @dan_zambon.
dl.acm.org
Graph deep learning methods have become popular tools to process collections of correlated time series. Unlike traditional multivariate forecasting methods, graph-based predictors leverage pairwise...
📢 Happy to finally share our paper on graph deep learning for time series forecasting!. This puts together what we've learned in the past few years using GNNs for TS processing, I hope you'll find it useful😃. W/ @IvanMarisca, @dan_zambon and Cesare 🔥. 🔗
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RT @FilippoMariaBi1: 🚀 We just released the code for our new #ICML2025 paper "Relational Conformal Prediction for Correlated Time Series" b….
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RT @ibrlworkshop: 📢 To align with other workshops, we extend the submission deadline to June 12th AoE! .🔗 Portal: .
sites.google.com
Call for Papers
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RT @ibrlworkshop: Introducing our 3rd Keynote 🎤. Ghada Sokar, Research Scientist at Google DeepMind and Adjunct Professor at Tu/e, will spe….
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RT @tgl_workshop: 💡deadline extension for our Temporal Graph Learning workshop: new deadline is May 25th, AOE 💡. looking forward to your su….
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Happy to share that CoRel has been accepted at ICML!🥳. CoRel quantifies uncertainty in correlated time series forecasting by leveraging graph deep learning operators. Check it out! 😎. W/ @alj_jenkins, Danilo, Cesare, and @FilippoMariaBi1 . 🔗
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RT @tgl_workshop: 🚨 15 days left! 🚨 .Don't miss the Call for Papers for the 3rd Temporal Graph Learning Workshop at KDD 2025 @kdd_news….
sites.google.com
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RT @AHendawy19: 📣Great News 🎉. Our Workshop on Inductive Biases in Reinforcement Learning (IBRL) @ibrlworkshop has been accepted @RL_Confer….
sites.google.com
About
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RT @ibrlworkshop: ✅ Works accepted at other venues are welcome if published after 1 September 2024.🔗 OpenReview portal: .
sites.google.com
Call for Papers
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RT @ibrlworkshop: 📢 The Call for Papers for the IBRL workshop is now open! 🚀.🤖 Topics: abstractions and structured policies, generalization….
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RT @tgl_workshop: 📢 Announcing the third edition of Temporal Graph Learning Workshop at KDD 2025 📢.📜 Call for Papers: Submit your work on T….
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RT @alj_jenkins: 🔬 A superb collaboration with @andreacini1994.and Prof. Alippi (@USI_en), @jobrkr, @arunsau_, @DrFuSiongNg and Prof. Mandi….
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RT @FilippoMariaBi1: Just published a new blog on 🎱 Pooling in #GraphNeuralNetworks! . 💡Learn the fundamentals through this gentle introduc….
gnn-pooling.notion.site
A gentle tutorial introduction to pooling in GNNs
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Happy to share that our paper on feudal graph RL, led by @tommaso_marzi, has been accepted at TMLR! 🎉. Feudal graph RL is a new paradigm for designing hierarchical RL agents by relying on hierarchical GNNs. Check it out! 😉. Link:
openreview.net
Graph-based representations and message-passing modular policies constitute prominent approaches to tackling composable control problems in reinforcement learning (RL). However, as shown by recent...
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Had an amazing time presenting the tutorial at the @LogConference with @IvanMarisca and @dan_zambon! 🚀. Looking forward to round 2 at the Italy meetup in Siena! 😊. Tutorial page:
gmlg.ch
The GMLG tutorial on graph deep learning for time-series processing.
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