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A case-based interpretable deep learning model for classification of mass lesions in digital mammography.

A. Barnett, F. Schwartz, C. Tao, C. Chen, Y. Ren, J. Lo, and C. Rudin. Nat. Mach. Intell., 3 (12): 1061-1070 (2021)

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Tao Tao

Tao Huu Phung

Christina Taouss

Madelaine Taoubi

Xue Tao

Other publications of authors with the same name

DyBit: Dynamic Bit-Precision Numbers for Efficient Quantized Neural Network Inference.J. Zhou, J. Wu, Y. Gao, Y. Ding, C. Tao, B. Li, F. Tu, K. Cheng, H. So, and N. Wong. CoRR, (2023)LiteGT: Efficient and Lightweight Graph Transformers.C. Chen, C. Tao, and N. Wong. CIKM, page 161-170. ACM, (2021)FAT: Frequency-Aware Transformation for Bridging Full-Precision and Low-Precision Deep Representations.C. Tao, R. Lin, Q. Chen, Z. Zhang, P. Luo, and N. Wong. IEEE Trans. Neural Networks Learn. Syst., 35 (2): 2640-2654 (February 2024)BATMANN: A Binarized-All-Through Memory-Augmented Neural Network for Efficient In-Memory Computing.Y. Ren, R. Lin, J. Ran, C. Liu, C. Tao, Z. Wang, C. Li, and N. Wong. ASICON, page 1-4. IEEE, (2021)Structured Pruning for Efficient Generative Pre-trained Language Models.C. Tao, L. Hou, H. Bai, J. Wei, X. Jiang, Q. Liu, P. Luo, and N. Wong. ACL (Findings), page 10880-10895. Association for Computational Linguistics, (2023)A Spectral Perspective towards Understanding and Improving Adversarial Robustness.B. Huang, R. Lin, C. Tao, and N. Wong. CoRR, (2023)A case-based interpretable deep learning model for classification of mass lesions in digital mammography.A. Barnett, F. Schwartz, C. Tao, C. Chen, Y. Ren, J. Lo, and C. Rudin. Nat. Mach. Intell., 3 (12): 1061-1070 (2021)FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware Transformation.C. Tao, R. Lin, Q. Chen, Z. Zhang, P. Luo, and N. Wong. CoRR, (2021)CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers.D. Shi, C. Tao, A. Rao, Z. Yang, C. Yuan, and J. Wang. CoRR, (2023)UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.D. Shi, C. Tao, Y. Jin, Z. Yang, C. Yuan, and J. Wang. ICML, volume 202 of Proceedings of Machine Learning Research, page 31292-31311. PMLR, (2023)

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Disambiguation of "Tao, Chaofan"

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A case-based interpretable deep learning model for classification of mass lesions in digital mammography.

Please choose a person to relate this publication to

Tao Tao

Tao Huu Phung

Christina Taouss

Madelaine Taoubi

Xue Tao

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Tao, Chaofan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A case-based interpretable deep learning model for classification of mass lesions in digital mammography.

Please choose a person to relate this publication to

Tao Tao

Tao Huu Phung

Christina Taouss

Madelaine Taoubi

Xue Tao

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

A case-based interpretable deep learning model for classification of mass lesions in digital mammography.