2 papers
cs.LG2021
SEEN: Sharpening Explanations for Graph Neural Networks using Explanations from Neighborhoods
Hyeoncheol Cho, Youngrock Oh, Eunjoo Jeon
Explaining the foundations for predictions obtained from graph neural networks (GNNs) is critical for credible use of GNN models for real-world problems. Owing to the rapid growth…
cs.CV2021
Towards Better Explanations of Class Activation Mapping
Hyungsik Jung, Youngrock Oh
Increasing demands for understanding the internal behavior of convolutional neural networks (CNNs) have led to remarkable improvements in explanation methods. Particularly, several…