Summit : Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Deep learning is increasingly used in decision-making tasks. However, understanding how neural networks produce final predictions remains a fundamental challenge. Existing work on interpreting neural network predictions for images often focuses on explaining predictions for single images or neurons....
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 26(2020), 1 vom: 22. Jan., Seite 1096-1106
|
|---|
| 1. Verfasser: |
Hohman, Fred
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Park, Haekyu,
Robinson, Caleb,
Polo Chau, Duen Horng |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2020
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics
|
|---|
| Schlagworte: | Journal Article
Research Support, U.S. Gov't, Non-P.H.S. |
|---|