Compact representation of graph data is a fundamental problem in pattern recognition and machine learning area. Recently, graph neural networks (GNNs) have been widely studied for graph-structured ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

Temporal Graph Representation Learning via Maximal Cliques Abstract: Graph Neural Networks (GNNs) have been proposed to learn graph representations for various graph mining tasks such as link ...

New research reveals a surprising geometric link between human and machine learning. A mathematical property called convexity ...

To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...