#graph-neural-networks
Every summary, chronological. Filter by category, tag, or source from the rail.
Tag · #graph-neural-networks
Mitigating Rollout Error in Graph World Models
Graph World Models (GWMs) face unique long-horizon errors where local inaccuracies propagate through topology. The Error-Aware GWM framework uses spectral regularization and critical-node weighting to maintain stability during dynamic-edge rollouts.
arXiv cs.AI
Understanding Graph Neural Networks: Architectures and Mechanisms
Graph Neural Networks (GNNs) enable machine learning on non-tabular, relational data by using message-passing mechanisms to aggregate information from neighboring nodes, allowing models to learn both local patterns and global graph structures.
IBM TechnologyShowing 2 of 2