Attribution Explanations for Deep Neural Networks: A Theoretical Perspective
- DOI
- 10.1109/tpami.2026.3667600
- Published
- 2026-07
- Container
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tpami.2026.3667600,
title = {Attribution Explanations for Deep Neural Networks: A Theoretical Perspective},
author = {Huiqi Deng and Hongbin Pei and Quanshi Zhang and Mengnan Du},
year = {2026},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
doi = {10.1109/tpami.2026.3667600},
url = {https://doi.org/10.1109/tpami.2026.3667600}
}RIS
TY - JOUR TI - Attribution Explanations for Deep Neural Networks: A Theoretical Perspective AU - Huiqi Deng AU - Hongbin Pei AU - Quanshi Zhang AU - Mengnan Du PY - 2026 JO - IEEE Transactions on Pattern Analysis and Machine Intelligence DO - 10.1109/tpami.2026.3667600 UR - https://doi.org/10.1109/tpami.2026.3667600 ER -
APA
Deng, H., Pei, H., Zhang, Q., & Du, M. (2026). Attribution Explanations for Deep Neural Networks: A Theoretical Perspective. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2026.3667600
Source records
- crossref · retrieved 2026-09-25T01:55:07.738Z