Graphormer
Graphormer is a Transformer-based graph neural network architecture that enhances the self-attention mechanism by introducing graph structural biases such as endpoint relations and spatial embeddings, making it suitable for modeling graph-structured data.
Timeline (last 90 days)
The paper "Joint Dynamic Lane Reversal and Variable Speed Limit Control: A Graphormer-Based Approach" proposes a joint control method based on Graphormer for dynamic lane reversal and variable speed limits.
Mainstream models in the molecular AI field are divided into three schools: GNN-based methods (e.g., SchNet, DimeNet++, Uni-Mol), Transformer-based methods (e.g., MolBERT, ChemBERTa, MoLFormer), and hybrid methods (e.g., GEM, Graphormer).
All Facts (2)
The paper "Joint Dynamic Lane Reversal and Variable Speed Limit Control: A Graphormer-Based Approach" proposes a joint control method based on Graphormer for dynamic lane reversal and variable speed limits.
50%UnverifiedMainstream models in the molecular AI field are divided into three schools: GNN-based methods (e.g., SchNet, DimeNet++, Uni-Mol), Transformer-based methods (e.g., MolBERT, ChemBERTa, MoLFormer), and hybrid methods (e.g., GEM, Graphormer).
50%