Heterogeneous graph representation learning seeks to map complex networks containing multiple types of nodes and relations into low-dimensional vector spaces while preserving semantic, structural and, ...

Agarwal, Chirag, Himabindu Lakkaraju, and Marinka Zitnik. "Towards a Unified Framework for Fair and Stable Graph Representation Learning." In Proceedings of the 37th Conference on Uncertainty in ...

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025, focusing on graph neural networks (GNNs), sequence-to-sequence (Seq2Seq) ...