EP-MAE: A resource-efficient masked autoencoding framework for 3D neural representation learning.
- DOI
- 10.1016/j.neunet.2026.109542
- Published
- 2026 Aug 22
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109542,
title = {EP-MAE: A resource-efficient masked autoencoding framework for 3D neural representation learning.},
author = {Zhu J and Zhao J and Lin C and Lyu L and Cai R and Ren X and Wu E},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109542},
url = {https://doi.org/10.1016/j.neunet.2026.109542}
}RIS
TY - JOUR TI - EP-MAE: A resource-efficient masked autoencoding framework for 3D neural representation learning. AU - Zhu J AU - Zhao J AU - Lin C AU - Lyu L AU - Cai R AU - Ren X AU - Wu E PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109542 UR - https://doi.org/10.1016/j.neunet.2026.109542 ER -
APA
J, Z., J, Z., C, L., L, L., R, C., X, R., & E, W. (2026). EP-MAE: A resource-efficient masked autoencoding framework for 3D neural representation learning.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109542
Source records
- pubmed · retrieved 2026-09-26T03:54:44.037Z
- europe-pmc · retrieved 2026-09-26T03:54:44.047Z