Are Large Language Models Good Temporal Graph Learners? Large Language Models (LLMs) have recently driven significant advancements in Natural Language Processing and various other applications. While a broad range of literature has explored the graph-reaso...

This week at the reading group, thursday, August 14th, 11am EDT (5pm CEST), @shenyanghuangtg.bsky.social will present: Are Large Language Models Good Temporal Graph Learners?

paper: arxiv.org/abs/2506.05393

zoom link on website

looking forward to seeing you! 🥳

escholarship.org/content/qt46...

Good news: The reading group starts again this thursday, july 24th, 11am EDT!

We are happy to welcome Zijie Huang (Google DeepMind) to present:
Neural Dynamics for Science: The Symbiosis of Deep Graph Learning and Differential Equations

Meet you on zoom (link on website) 🎉🥳

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

looking forward to your submissions!

Submission deadline for our #kdd2025
workshop is in 6 days, on May 20th AOE.😌

Topics include: Frontiers, Applications, Theory, Models, Methods and Evaluation for learning on temporal graphs!

Position papers, extended abstracts and standard papers.

The venue is non-archival.

📚 This week's reading group:
🗓 Thursday, May 1st | 🕚 11am EDT
🎙 Jason Schoeters (Univ. of Florence, DISIA Lab) presents:
Spanners in Temporal Graphs
🔗 Paper | www.sciencedirect.com/science/arti...
🪩zoom link on website.

#Graph #TemporalGraph

TGB-Seq Benchmark: Challenging Temporal GNNs with Complex... Future link prediction is a fundamental challenge in various real-world dynamic systems. To address this, numerous temporal graph neural networks (temporal GNNs) and benchmark datasets have been...

This week at the Reading Group, Lu Yi from ALGO Lab will present: TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics (#ICLR 2025).

See you on thursday, april 24th, 11am EDT 🌟
zoom link on website!

openreview.net/forum?id=8e2...

Temporal Heterogeneous Graph Generation with Privacy, Utility, and... Nowadays, temporal heterogeneous graphs attract much research and industrial attention for building the next-generation Relational Deep Learning models and applications, due to their informative...

☀️This week at the reading group, Thursday, April 17th, 11am EDT, Xinyu He will present:

Temporal Heterogeneous Graph Generation with Privacy, Utility, and Efficiency (ICLR 2025 Spotlight)

Looking forward to seeing you there!
zoom link on website

paper: openreview.net/forum?id=tj5...

Reviewer Recruitment: TGL Workshop@ KDD 2025 Thank you for your interest in reviewing research submissions for the Temporal Graph Learning Workshop@ KDD 2025. Please fill out the information in this form, so we can know more about your backgroun...

🌟Call for Reviewers!🌟
We are currently recruiting reviewers for our upcoming workshop and would love to have your expertise on board!

Timeline: May 2025

📝 Please sign up here: docs.google.com/forms/d/e/1F...

Thank you for supporting the workshop!

🚀 Time zone update: CET → CEST! 🚀

Join us at the Reading Group this Thursday, April 10, 11 AM EDT / 5 PM CEST! 🎙️

🔹 Speaker: Veronica Lachi (FBK)
🔹 Paper: Boosting Relational Deep Learning with Pretrained Tabular Models
🔹 Zoom link on website

arxiv.org/pdf/2504.04934

TGL Workshop 2025 Key dates

📢 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)

sites.google.com/view/tgl-wor...

Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements Catheter ablation of Atrial Fibrillation (AF) consists of a one-size-fits-all treatment with limited success in persistent AF. This may be due to our inability to map the dynamics of AF with the limit...

paper link: arxiv.org/abs/2502.09473

❤️ This week, March 27th, 11am EDT, we are looking forward to have Alexander Jenkins, who will present: Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements ❤️

zoom link on our website!

The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges Homophily principle, \ie{} nodes with the same labels or similar attributes are more likely to be connected, has been commonly believed to be the main reason for the superiority of Graph Neural Networ...

This week at the Reading Group, we are happy to welcome Sitao Luan, who will present: The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges

See you on thursday, March 20, 11am EDT on zoom (link on website)

arxiv.org/abs/2407.09618

🚨🌺 Time zone update: EST → EDT!

📅 Reading Group: Thursday, March 13 🕚 11 AM EDT

This week, Zifeng Ding presents DyGMamba – Efficiently Modeling Long-Term Temporal Dependency on Continuous-Time Dynamic Graphs with State Space Models.

arxiv.org/pdf/2408.047...

Using Time-Aware Graph Neural Networks to Predict Temporal... Node centralities play a pivotal role in network science, social network analysis, and recommender systems. In temporal data, static path-based centralities like closeness or betweenness can give...

openreview.net/forum?id=6n7...

📢Join us Thursday, March 6, at 11 AM (ET) on Zoom (link on website) for a discussion on:

🧠 Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs (NeurIPS 2024)

👥 Presented by Franziska Heeg (JMU Würzburg)

UTG: Towards a Unified View of Snapshot and Event Based Models for... Many real world graphs are inherently dynamic, constantly evolving with node and edge additions. These graphs can be represented by temporal graphs, either through a stream of edge events or a...

📄 Paper: openreview.net/forum?id=ZKH...

UTG: Towards a Unified View of Snapshot and Event Based Models for... Many real world graphs are inherently dynamic, constantly evolving with node and edge additions. These graphs can be represented by temporal graphs, either through a stream of edge events or a...

This Thursday, Feb 27th, 11am EDT join us for

"UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs" (LOG 2024 @logconference.bsky.social )

🎤 Presenter: Our very own organizer Andy @shenyanghuangtg.bsky.social (McGill University, Mila)

🔗 Zoom link on website

[Re] Reproducibility Study of “Explaining Temporal Graph Models... This paper seeks to reproduce and extend the results of the paper “Explaining Temporal Graph Models Through an Explorer-Navigator Framework” by (Xia et al., 2023). The main contribution of the...

paper link: openreview.net/forum?id=9M2...

Tomorrow, thursday, feb 20th, 11am EDT, Andreas Berentzen @andreasberentzen.bsky.social and Jesse Wonnink will present their Reproducibility study of: Explaining Temporal Graph Models Through an Explorer-Navigator Framework (TMLR and NeurIPS Journal Track).

🪩
zoom link on website

Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed _Graph Neural Tangent Kernel_ (GNTK) fuses graph neural networks and graph kernels, simplifies the process of graph representation learning, interprets the training dynamics of graph neural...

This thursday, Feb 13th, 11am ET, at the Reading group, Katherine Tieu will present: Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed (NeurIPS 2024).
Looking forward to seeing you there! 🎉🎉
Zoom link on website

openreview.net/forum?id=266...

links to papers:
openreview.net/pdf/f7ebe840...
and
openreview.net/pdf/b3c2dec3...

This week we look forward to an exciting talk featuring two #LOG2024 papers!
📢 Towards Neural Scaling Laws on Graphs & Do Neural Scaling Laws Exist on Graph Self-Supervised Learning?
🎤 Jingzhe Liu (MSU) & Qian Ma (RPI)
📅 11am EST, Feb 6 (Thu)
📍 Zoom (link on website)
Don’t miss it! 🔥

🕵️‍♀️This week at the Reading Group, Tim Poštuvan will present Learning-Based Link Anomaly Detection in Continuous-Time Dynamic Graphs (TMLR)

⏰Thursday, Jan 30th, 11am EST
📍zoom, link on our website
📃https://openreview.net/forum?id=8imVCizVEw

See you there

📹This talk is now available on our YouTube channel:
youtu.be/GWFtIffcE0M

We created a starter pack for temporal graph researchers!
Please let us know if you would like to be added, or know someone to be added ✨

go.bsky.app/Z7X5KH

🚨 The Temporal Graph Learning Reading Group is back from winter break! 🚨

📅 Thursday, Jan 16th, 11am ET (on Zoom)
📖 Topic: Interpreting Temporal Graph Neural Networks with Koopman Theory
👨‍🔬 Speaker: Michele Guerra
📄 Paper: arxiv.org/pdf/2410.13469
🔗 Zoom link: Check our website!

See you on thursday!

The recording for RELBENCH: A Benchmark for Deep Learning on Relational Databases is now on YouTube: youtu.be/2idUm4OBX7Y

Enjoy!🪩

The recording for Expressive Power of Temporal Message Passing is now on YouTube: youtu.be/Jb6GgR-ZbFI

Enjoy 🎈