Jun 20, 2024 · In the multi-head attention model, each head focus on learning information from different neighborhood orders. This allows for learning at an ...
Multi-Head Attention Ordering. We can also employ multi-head attention to provide additional representational power to our model. We see several advantages ...
The Graph Attention Network (GAT) is a type of graph neural network (GNN) that uses attention mechanisms to weigh the importance of nodes' neighbors, ...
Oct 5, 2024 · We introduce GATE-SR, a novel model that leverages a multi-head graph attention autoencoder to capture indirect social influence from higher-order neighbors.
Nov 19, 2024 · In the first network layer, we use 8 higher-order attention heads, and 1 in the subsequent layers. ... Multi-hop attention graph neural network.
We propose a novel graph attention network with adaptability that could fully utilize the features of multi-order content.
In this paper, we propose a novel graph neural network - Spatial-Temporal Multi-head Graph ATtention network (ST-MGAT), to deal with the traffic forecasting ...
Oct 22, 2024 · The Graph Attention Network (GAT) is a type of graph neural network (GNN) that uses attention mechanisms to weigh the importance of nodes' ...
In this paper, we propose a multi-head attention graph neural network (MAE-GNN) for session-based recommendation by combining a dual-gated graph neural network ...
Here we pro- pose Multi-hop Attention Graph Neural Network. (MAGNA), a principled way to incorporate multi- hop context information into every layer of atten-.
Missing: order | Show results with:order