「GNN」の検索結果
12 件Industrial fraud detection often relies on costly expert-crafted features that overlook graph-structured relat
Designing foundation models for graphs is challenging due to the irregular structure of graphs and the differe
Standard open-set node classification methods rely on the homophily assumption, where connected nodes share la
Robotic construction offers the potential to use materials more efficiently and create complex geometries, but
Temporal graph learning models the evolution of dynamic systems, where both structural interactions and semant
Tensegrity robots offer lightweight, compliant mobility over challenging terrain but remain difficult to model
We study the use of graph neural networks (GNNs) for finding approximate ground states of Ising models. Effici
Physics-informed neural networks (PINNs) represent a growing frontier in using artificial intelligence to solv
Large-scale logistics networks require synthetic data generation capabilities to support scenario-based planni
Graph neural networks (GNNs) are a class of neural networks suitable for learning on graph-structured data. Th
Finding a representative description of graph entities that captures their structural roles and homophily is a
Inventory and distribution planning in Physical Internet networks requires coordinating factory-hub assignment