6 citations · 7 across the 8 of their papers we have counts for
8 papers
Self-Exploring Language Models for Explainable Link Forecasting on Temporal Graphs via Reinforcement Learning
Zifeng Ding, Shenyang Huang, Zeyu Cao +11
Forecasting future links is a central task in temporal graph (TG) reasoning, requiring models to leverage historical interactions to predict upcoming ones. Traditional neural appro…
TGM: a Modular and Efficient Library for Machine Learning on Temporal Graphs
Jacob Chmura, Shenyang Huang, Tran Gia Bao Ngo +7
Well-designed open-source software drives progress in Machine Learning (ML) research. While static graph ML enjoys mature frameworks like PyTorch Geometric and DGL, ML for temporal…
UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs
Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany +2
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…
MiNT: Multi-Network Training for Transfer Learning on Temporal Graphs
Kiarash Shamsi, Tran Gia Bao Ngo, Razieh Shirzadkhani +7
Temporal Graph Learning (TGL) has become a robust framework for discovering patterns in dynamic networks and predicting future interactions. While existing research has largely con…
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
Julia Gastinger, Shenyang Huang, Mikhail Galkin +9
Multi-relational temporal graphs are powerful tools for modeling real-world data, capturing the evolving and interconnected nature of entities over time. Recently, many novel model…
Temporal Graph Rewiring with Expander Graphs
Katarina Petrović, Shenyang Huang, Farimah Poursafaei +1
Evolving relations in real-world networks are often modelled by temporal graphs. Temporal Graph Neural Networks (TGNNs) emerged to model evolutionary behaviour of such graphs by le…
On the Scalability of GNNs for Molecular Graphs
Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei +4
Scaling deep learning models has been at the heart of recent revolutions in language modelling and image generation. Practitioners have observed a strong relationship between model…
Temporal Graph Analysis with TGX
Razieh Shirzadkhani, Shenyang Huang, Elahe Kooshafar +2
Real-world networks, with their evolving relations, are best captured as temporal graphs. However, existing software libraries are largely designed for static graphs where the dyna…