Tag: Causal Graph Neural Networks
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EquiformerV3: Fast, Expressive SE(3) Graph Transformers
Discover EquiformerV3, the efficient and expressive SE(3)-equivariant graph attention transformer optimized for large-scale 3D atomistic modeling.
Neighbourhood Transformer: Advanced Graph Learning with Switchable Attention
Discover Neighbourhood Transformer, a monophily-aware graph learning model using switchable attention for improved performance on heterophilic and homophil...
k-Maximum Inner Product Attention Boosts Graph Transformers
Discover how k-Maximum Inner Product attention enhances graph transformers with linear complexity and high expressiveness for large-scale graph learning.
BadImplant: Multi-Targeted Injection Backdoor Attack on GNNs
Discover BadImplant, a novel injection-based multi-targeted backdoor attack on graph neural networks that preserves graph integrity and evades defenses.
Optimized Routing in LEO Mega-Constellations Using AI
Discover how AI-driven intent compilation enhances constrained routing efficiency and safety in LEO mega-constellations with 99.8% delivery success.