🔥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

🎉 The course "Time series analysis with Python" is out! 💡 Dive into a comprehensive introduction to time series analysis, filled with coding examples and exercises. 💻 Gain practical skills and master fundamental techniques. Check it out here: github.com/FilippoMB/pyth…

*Kolmogorov-Arnold Networks (KANs)* by Ziming Liu et al. Since everyone is talking about KANs, I wrote some notes on Notion with a few research questions I find interesting. First time I do something like this, give me some feedback. 🙃 sscardapane.notion.site/Kolmogorov-Arn…

It was really a pleasure to be invited at the West Norway University of Applied Science as the opponent for the PhD thesis of Michele Gazzea. Excellent work, both the defendant and his supervisor Reza Arghandeh!

🇫🇷 Next week I'll be in Paris attending #SIAMLA24. I'll give a talk about our recent work on Total Variation Graph Neural Networks, first presented at ICML last year github.com/FilippoMB/Tota… Looking forward to discussions about graphs, machine learning, and optimization!

🧵 Ready for #ICML2024! This year me and Filippo Maria Bianchi 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👇

Come to visit me and Ivan Marisca tomorrow at the first poster session (11:30-13:00 - Hall C) as we present our paper #1016! #ICML2024

🤔 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…

3. Graph Deep Learning for Time Series Processing: Forecasting, Reconstruction, and Analysis by Andrea Cini, Ivan Marisca, Daniele Zambon 4. Integrating Knowledge Graphs and Large Language Models for Advancing Scientific Research by Qiang Zhang, Jiaoyan Chen, Zaiqiao Meng @ ACL 2025

Our new featured LoG2024 meetup will be held in the Artic❄️ Tromsø🇳🇴Meetup info: Date-> 27 Nov. 2024 Website-> sites.google.com/view/log-troms…

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

🔥 Bayesian nonparametrics meets pooling in GNNs! 🔥 This is the first clustering-based pooling method that learns and dynamically adapts the size of the pooled graph to input and downstream task. 📄 paper: arxiv.org/abs/2501.09821 💻 code: github.com/NGMLGroup/Baye…

🎉 Our paper was accepted to #ICLR2025! Project page: github.com/NGMLGroup/MaxC…

Big personal update 😊 I'm moving to University of Oxford to work with Michael Bronstein on my recently funded Swiss National Science Foundation project 🎉🎉 As part of the project, I'll also be collaborating with Filippo Maria Bianchi 😃 Looking forward to exciting new research & collabs! 😎

Not happy with the review process at #ICML2025. 6 reviews in 1 month are too much: review quality and engagement in the rebuttal will be low. Also, the 12 (!!) mandatory questions are often irrelevant. Why comment on the supplementary if a major flaw (e.g. plagiarism) is found?!

Join us to hear talks from great experts logml.ai/speaker.html Marinka Zitnik Tolga Birdal Filippo Maria Bianchi Coralia Cartis, Marco Cuturi, Estelle Massart, Bastian Grossenbacher-Rieck, Francisco Ruiz, Alice Barbara Tumpach

Tomorrow (April 26th), I'll present our recent work on MAXCUT with GNNs for graph pooling at #ICLR2025 Stop by to say hi at Poster 215 from 10:00 to 12:30 ☺️

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

🚀 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

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!

🚨 Exciting news! We released 🎱 tgp (Torch Geometric Pool), the library for pooling in Graph Neural Networks. 🚀 Get started with our tutorials: torch-geometric-pool.readthedocs.io/en/latest/tuto… With Ivan Marisca and Carlo Abate. #GraphML #GNN #Pooling #Pyg