Tag: Causal Graph Neural Networks
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Adaptive Node Classification for Heterophily in Multiplex Graphs
Discover an adaptive method for node classification in multiplex graphs that models heterophily and improves accuracy across diverse network types.
Unified Graph Representation Learning Across Multi-Level Abstractions
Discover a unified framework for graph representation learning using multi-level abstractions and adaptive self-weighting to boost classification and clust...
Robust Federated Multimodal Graph Learning Solutions
Discover FedMPO, a robust federated multimodal graph learning framework tackling modality heterogeneity and enhancing model performance.
SP-GCRL: Advanced Influence Maximization on Incomplete Graphs
Discover SP-GCRL, a novel framework using reinforcement learning to maximize influence on incomplete social graphs with high efficiency and scalability.
GraphMind: Building Human-Like Social Networks with LLM Bots
Discover how GraphMind enhances LLM bots to form human-like social networks, challenging current detection methods with advanced graph-based AI.