Ensembling Visual Explanations

By Nazneen Rajani, Raymond J. Mooney. 2018

5 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Safety, Robustness & Interpretability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Francisco Herrera
2. Salvador Garcia
3. Daniel Molina
4. Javier Del Ser
5. Adrien Bennetot
6. Alejandro Barredo Arrieta
7. Sergio Gil-Lopez
8. Natalia Díaz Rodríguez

In Computer Vision and Pattern Recognition

1. Salvador Garcia
2. Francisco Herrera
3. Adrien Bennetot
4. Alejandro Barredo Arrieta
5. Sergio Gil-Lopez
6. Daniel Molina
7. Natalia Díaz Rodríguez
8. Raja Chatila

In Safety, Robustness & Interpretability

1. Adrien Bennetot
2. Francisco Herrera
3. Natalia Díaz Rodríguez
4. Raja Chatila
5. Salvador Garcia
6. Javier Del Ser

Citations in the corpus

• Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI (2019, positive): “…and multiple classifier systems in addition to Deep Learning models; the combination of explanation maps of multiple clas-sifiers to produce improved explanations of the ensemble to which they belong [243] ; and recent insights dealing with traditional and gradient boosting ensembles [287,288] .”