Summary of Talos: a More Effective and Efficient Adversarial Defense For Gnn Models Based on the Global Homophily Of Graphs, by Duanyu Li et al.
Talos: A More Effective and Efficient Adversarial Defense for GNN Models Based on the Global…
Talos: A More Effective and Efficient Adversarial Defense for GNN Models Based on the Global…
GraphAlign: Pretraining One Graph Neural Network on Multiple Graphs via Feature Alignmentby Zhenyu Hou, Haozhan…
RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Networkby Yunbo Hou, Haoran Ye, Yingxue Zhang,…
Bayesian Mesh Optimization for Graph Neural Networks to Enhance Engineering Performance Predictionby Jangseop Park, Namwoo…
In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphsby Grzegorz Kaszuba, Amirhossein D.…
Towards a General Recipe for Combinatorial Optimization with Multi-Filter GNNsby Frederik Wenkel, Semih Cantürk, Stefan…
GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoningby Costas Mavromatis, George KarypisFirst submitted to…
LSPI: Heterogeneous Graph Neural Network Classification Aggregation Algorithm Based on Size Neighbor Path Identificationby Yufei…
Rethinking Pruning for Backdoor Mitigation: An Optimization Perspectiveby Nan Li, Haiyang Yu, Ping YiFirst submitted…
Enhancing Sustainable Urban Mobility Prediction with Telecom Data: A Spatio-Temporal Framework Approachby ChungYi Lin, Shen-Lung…