🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

🤔 How to interpret spatio-temporal data and deep learning models? 💡In our recent work with Michele Guerra and Simone Scardapane we leverage Koopman theory to design an XAI framework for spatio-temporal GNNs. 📄 Preprint: arxiv.org/abs/2410.13469 💻 Code: github.com/NGMLGroup/Koop…

Can't wait! 🔥

Had an amazing time presenting the tutorial at the Learning on Graphs Conference 2025 with Ivan Marisca and Daniele Zambon! 🚀 Looking forward to round 2 at the Italy meetup in Siena! 😊 Tutorial page: gmlg.ch/tutorials/grap…

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/forum?id=wFcyJ…

Just published a new blog on 🎱 Pooling in #GraphNeuralNetworks! 💡Learn the fundamentals through this gentle introduction and discover how they can improve your GNN applications. 👉 Check it out here: gnn-pooling.notion.site #GNN #MachineLearning #AI

🔬 A superb collaboration with Andrea Cini and Prof. Alippi (USI University), Joseph Barker, Arun Sau, Fu Siong Ng and Prof. Mandic (Imperial College London, Imperial CardiacEP.AI, AI4Health Center) and collaborators at University of Oxford ❤️ 📄Preprint: arxiv.org/abs/2502.09473 5/5

📣Great News 🎉 Our Workshop on Inductive Biases in Reinforcement Learning (IBRL) Inductive Biases in RL has been accepted RL_Conference (RLC), 2025. Interested in submitting your paper or participating as a reviewer? Check our website for more details: sites.google.com/view/ibrl-work…

📢 Announcing the third edition of Temporal Graph Learning Workshop at KDD 2025 📢 📜 Call for Papers: Submit your work on Temporal Graphs, Evolving Relational Data, Spatio-Temporal Graphs & more! 📅 Submission Deadline: May 20 AoE (Openreview)

📢 The Call for Papers for the IBRL workshop is now open! 🚀 🤖 Topics: abstractions and structured policies, generalization, relational biases and representations, biases for robotics, future directions, and more 🗓️ Submission Deadline: 30th May 2025, AoE 📙 Format: 4-8 pages

✅ Works accepted at other venues are welcome if published after 1 September 2024 🔗 OpenReview portal: openreview.net/group?id=rl-co… 📝 If you want to participate as a reviewer, check: docs.google.com/forms/d/e/1FAI… 🌐 For more information, check: sites.google.com/view/ibrl-work…

🚨 15 days left! 🚨 Don't miss the Call for Papers for the 3rd Temporal Graph Learning Workshop at KDD 2025 SIGKDD 2025 📅 Deadline: May 20 (OpenReview) 🔗sites.google.com/view/tgl-works…

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/ Alexander Jenkins, Danilo, Cesare, and Filippo Maria Bianchi 🔗 arxiv.org/abs/2502.09443

💡deadline extension for our Temporal Graph Learning workshop: new deadline is May 25th, AOE 💡 looking forward to your submissions!

Introducing our 3rd Keynote 🎤 Ghada Sokar, Research Scientist at Google DeepMind and Adjunct Professor at Tu/e, will speak on "Network Plasticity and Scalability in Deep Reinforcement Learning" — exploring model adaptation and continuous learning under non-stationary conditions

📢 To align with other workshops, we extend the submission deadline to June 12th AoE! 🔗 Portal: openreview.net/group?id=rl-co… 🌐 More information at: sites.google.com/view/ibrl-work… 🚀 Looking forward to seeing you at RL_Conference!

🚀 We just released the code for our new #ICML2025 paper "Relational Conformal Prediction for Correlated Time Series" by Andrea Cini and co-authors! 💻 code: github.com/andreacini/cor… 📑 paper: arxiv.org/abs/2502.09443

Freshly accepted as a tutorial paper in ACM Computing Surveys! 🥳 Check out the updated version: dl.acm.org/doi/abs/10.114… cc Ivan Marisca Daniele Zambon

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!

🚨 ICML 2025 Paper 🚨 "On Measuring Long-Range Interactions in Graph Neural Networks" We formalize the long-range problem in GNNs: 💡Derive a principled range measure 🔧 Tools to assess models & benchmarks 🔬Critically assess LRGB 🧵 Thread below 👇 #ICML2025