Interpretability, Reproducibility, and Replicability [From the Guest Editors]-Reference-Cited by-同舟云学术

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Interpretability, Reproducibility, and Replicability [From the Guest Editors]

Published:2022-07 Issue:4 Volume:39 Page:5-7
ISSN:1053-5888
Container-title:IEEE Signal Processing Magazine
language:
Short-container-title:IEEE Signal Process. Mag.

Author:

Adali Tulay¹,Guido Rodrigo Capobianco²,Ho Tin Kam³,Muller Klaus-Robert⁴,Strother Stephen⁵

Affiliation:

1. Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, Maryland, USA

2. Associate Professor, São Paulo State University (UNESP), São José do Rio Preto, São Paulo, Brazil

3. Senior Artificial Intelligence Scientist, IBM Watson Health, Yorktown Heights, New York, USA

4. Computer Science, TU Berlin, Germany

5. Medical Biophysics, University of Toronto, Toronto, Ontario, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/79/9810027/09810056.pdf?arnumber=9810056

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1. Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods;Earth and Space Science;2024-07

2. An Exciting Juncture for Signal Processing Research: On Building Bridges, Challenges, and Opportunities [From the Editor];IEEE Signal Processing Magazine;2024-04-16

3. Interpretability of Machine Learning: Recent Advances and Future Prospects;IEEE MultiMedia;2023-10

4. RETSINA: Reproducibility and Experimentation Testbed for Signal-Strength Indoor Near Analysis;2023 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN);2023-09-25

5. An Indoor Fall Monitoring System: Robust, Multistatic Radar Sensing and Explainable, Feature-Resonated Deep Neural Network;IEEE Journal of Biomedical and Health Informatics;2023-04

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