link prediction
Link prediction is a task in graph-based learning where the goal is to predict the existence of a connection between two entities in a network, often applied in social networks and recommendation systems.
- $\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
- Adaptive Cannistraci-Hebb Network Automata Modelling of Complex Networks for Path-based Link Prediction
- Brain network science modelling of sparse neural networks enables Transformers and LLMs to perform as fully connected
- Bridging Theory and Practice in Link Representation with Graph Neural Networks
- Future Link Prediction Without Memory or Aggregation
- Joint Hierarchical Representation Learning of Samples and Features via Informed Tree-Wasserstein Distance
- OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction
- Pseudo-Riemannian Graph Transformer
- Robust Explanations of Graph Neural Networks via Graph Curvatures
- SALoM: Structure Aware Temporal Graph Networks with Long-Short Memory Updater
- Scalable Feature Learning on Huge Knowledge Graphs for Downstream Machine Learning
- Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
- Transfer Learning on Edge Connecting Probability Estimation Under Graphon Model