Original post on xn--baw-joa.social

Advances in temporal graph reasoning to be presented at #ECAI

Researchers from the AI Institute at the University of Stuttgart will present a paper tackling key challenges in temporal graph learning. The work, titled “Full-History Graphs with Edge-Type Decoupled Networks for Temporal Reasoning […]

TGLib: An Open-Source Library for Temporal Graph Analysis We initiate an open-source library for the efficient analysis of temporal graphs. We consider one of the standard models of dynamic networks in which each edge has a discrete timestamp and transition ...

🚀 TGLib is now on PyPI!
Our open-source library for efficient temporal graph analysis is now easy to install (Linux):

pip install temporalgraphlib

📄 Paper: arxiv.org/abs/2209.12587

💻 Code: gitlab.com/tgpublic/tglib

#TGLib #TemporalGraphs #Python #OpenSource #NetworkScience

An Edge-Based Decomposition Framework for Temporal Networks A temporal network is a dynamic graph where every edge is assigned an integer time label that indicates at which discrete time step the edge is available. We consider the problem of hierarchically dec...

🚀Our WSDM'25 paper introduces a new edge-based framework for decomposing temporal networks.

⚡️Scales to 100M+ edges, reveals structures in dynamic data—eg, misinformation patterns on Twitter

📄 arxiv.org/abs/2309.11843

With A.Konstantinidis & G.Italiano
#temporalgraphs #graphmining #misinformation

We welcome full papers, position papers, and extended abstracts on Frontiers, Applications, Theory, Methods and Evaluation of Temporal Graphs. Find the full call for paper on our website

#KDD2025 #TemporalGraphs #MachineLearning

Position: Relational Deep Learning - Graph Representation Learning on Relational Databases Much of the world’s most valued data is stored in relational databases and data warehouses, where the data is organized into tables connected by primary-foreign key relations. However, building mac...

Hi!
This thursday, nov 21st, 11am EST, Rishabh Ranjan will present:
RELBENCH: A Benchmark for Deep Learning on Relational Databases (NeurIPS 2024 Datasets and Benchmarks Track)
🎈
Join on zoom (link on website)

arxiv.org/pdf/2407.20060

#graphml #machinelearning #temporalgraphs #neurips