optimale
ScoreCAM GNN: une explication optimale des r\'eseaux profonds sur graphes
Raison, Adrien, Bourdon, Pascal, Helbert, David
The explainability of deep networks is becoming a central issue in the deep learning community. It is the same for learning on graphs, a data structure present in many real world problems. In this paper, we propose a method that is more optimal, lighter, consistent and better exploits the topology of the evaluated graph than the state-of-the-art methods.
Country:
- North America > United States > Washington > King County > Seattle (0.04)
- North America > United States > Nevada > Clark County > Las Vegas (0.04)
- North America > United States > Hawaii > Honolulu County > Honolulu (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.34)