A Survey of Computationally Efficient Graph Neural Networks for Reconfigurable Systems
Graph neural networks (GNNs) are powerful models capable of managing intricate
connections in non-Euclidean data, such as social networks, physical systems, chemical …
connections in non-Euclidean data, such as social networks, physical systems, chemical …
Improved PMGAT for Human-Object Interaction Detection through Graph Sampling-based Dynamic Edge Strategy (GraphSADES)
One of the challenges in training graph neural networks (GNNs) applied to human-object
interaction (HOI) is the computational complexity associated with updating and aggregating …
interaction (HOI) is the computational complexity associated with updating and aggregating …