A Denoising Adversarial Model Based on Hyperellipsoidal Knowledge Representation Learning for DTI Prediction.
- DOI
- 10.1109/tcbbio.2026.3710670
- Published
- 2026 Sep-Oct
- Container
- IEEE transactions on computational biology and bioinformatics
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tcbbio.2026.3710670,
title = {A Denoising Adversarial Model Based on Hyperellipsoidal Knowledge Representation Learning for DTI Prediction.},
author = {Yang C and Xiong F and Luo Y and Wang F},
year = {2026},
journal = {IEEE transactions on computational biology and bioinformatics},
doi = {10.1109/tcbbio.2026.3710670},
url = {https://doi.org/10.1109/tcbbio.2026.3710670}
}RIS
TY - JOUR TI - A Denoising Adversarial Model Based on Hyperellipsoidal Knowledge Representation Learning for DTI Prediction. AU - Yang C AU - Xiong F AU - Luo Y AU - Wang F PY - 2026 JO - IEEE transactions on computational biology and bioinformatics DO - 10.1109/tcbbio.2026.3710670 UR - https://doi.org/10.1109/tcbbio.2026.3710670 ER -
APA
C, Y., F, X., Y, L., & F, W. (2026). A Denoising Adversarial Model Based on Hyperellipsoidal Knowledge Representation Learning for DTI Prediction.. IEEE transactions on computational biology and bioinformatics. https://doi.org/10.1109/tcbbio.2026.3710670
Source records
- pubmed · retrieved 2026-11-10T11:59:22.529Z