Andrea Cini

🇨🇭 SNSF Postdoc at @EPFL. - Time series and graphs

[Mathieu @miniapeur]

As far as I know, we cannot choose the exact number of papers we review at top conferences. This means I review much less than I would actually like to. I would sincerely be happy to review two papers for each top conference (ICLR, NeurIPS, ICML, AISTATS, etc.), but being asked to review five to seven papers per conference is far too much.

[Valentina Moretti @Vale__moretti]

Tomorrow, I’ll present our work “What Matters in Deep Learning for Time Series Forecasting?” at the #EurIPS workshop on Benchmarking and Evaluating AI. Come by for a chat if you’re around!
Many thanks to @andreacini1994 , @IvanMarisca , and Cesare Alippi

[Antonio Norelli @noranta4]

How to tamper with a gas meter to pay lower bills?

This is the story of how a supposedly aligned open source LLM, perhaps not even knowing how to do it, will give you the right instructions. (1/3)
https://t.co/2SzbatO3mq

[Andrea Cini @andreacini1994]

🎉 Honored to receive the Informatics Europe Best Dissertation Award 2025 for my PhD thesis!

Beyond grateful to my advisor Cesare, my amazing collaborators, and all the people at @USI_university!

🙏🙏

🔗 https://t.co/w6WlfdbkZN

[Shenyang Huang @shenyangHuang]

Introducing TGM: Temporal Graph ML, Reimagined 🚀
The first open-source library unifying discrete & continuous-time GNNs under one API, built for speed, flexibility & research on temporal graphs.
🌟https://t.co/eOAzImDdbs

[Roberto Neglia @beertorob]

📢 New preprint available!

We propose ResCP, a novel training-free conformal prediction method for time series.

🔗 Read the preprint: https://t.co/Ep0Wta7iTp

🤝 @andreacini1994, @mmbronstein, @FilippoMariaBi1

#conformalprediction #timeseries #reservoircomputing

[Andrea Cini @andreacini1994]

Closing out August in the Arctic, cooking up cool new research with @FilippoMariaBi1 and @beertorob!

Stay tuned 👀🏔️

[TGL Workshop @tgl_workshop]

Join the Temporal Graph Learning Workshop at KDD 2025, we have an amazing program with great speakers and papers waiting for you. Let's shape together the future of temporal graph research.
📍Aug 4 | 1–5 PM | Room 714A, Toronto Convention Center
🔗 https://t.co/y8DSq83b5b

[Jacob Bamberger @jacobbamb]

🚨 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

[Andrea Cini @andreacini1994]

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!

[Andrea Cini @andreacini1994]

Freshly accepted as a tutorial paper in ACM Computing Surveys! 🥳

Check out the updated version: https://t.co/bboAZQSFmA

cc @IvanMarisca @dan_zambon

[Andrea Cini @andreacini1994]

📢 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 🔥

🔗https://t.co/ypeovJoRLI

[Filippo Maria Bianchi @FilippoMariaBi1]

🚀 We just released the code for our new #ICML2025 paper "Relational Conformal Prediction for Correlated Time Series" by @andreacini1994 and co-authors!

💻 code: https://t.co/CK1JwPySdY
📑 paper: https://t.co/tSp5WD558q

[Inductive Biases in RL @ibrlworkshop]

📢 To align with other workshops, we extend the submission deadline to June 12th AoE!
🔗 Portal: https://t.co/NIuF9Bn8yA
🌐 More information at: https://t.co/52SKuE33vS
🚀 Looking forward to seeing you at @RL_Conference!

[Inductive Biases in RL @ibrlworkshop]

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

[TGL Workshop @tgl_workshop]

💡deadline extension for our Temporal Graph Learning workshop: new deadline is May 25th, AOE 💡

looking forward to your submissions!

[Andrea Cini @andreacini1994]

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

🔗 https://t.co/O2rWbeQAl6

[TGL Workshop @tgl_workshop]

🚨 15 days left! 🚨
Don't miss the Call for Papers for the 3rd Temporal Graph Learning Workshop at KDD 2025 @kdd_news

📅 Deadline: May 20 (OpenReview)
🔗https://t.co/UPvUGtrKml

[Ahmed Hendawy @ RSS 2026 @AHendawy19]

📣Great News 🎉

Our Workshop on Inductive Biases in Reinforcement Learning (IBRL) @ibrlworkshop has been accepted @RL_Conference (RLC), 2025.

Interested in submitting your paper or participating as a reviewer? Check our website for more details:
https://t.co/xc3F923xzH

[Inductive Biases in RL @ibrlworkshop]

✅ Works accepted at other venues are welcome if published after 1 September 2024
🔗 OpenReview portal: https://t.co/NIuF9Bn8yA
📝 If you want to participate as a reviewer, check: https://t.co/7uwkOxIzU8
🌐 For more information, check: https://t.co/52SKuE33vS