An Uncertainty-Aware Ensemble Approach to Modeling Utility of Pseudolabels for Semisupervised Learning
- DOI
- 10.1109/tnnls.2026.3696935
- Published
- 2026-11
- Container
- IEEE Transactions on Neural Networks and Learning Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2026.3696935,
title = {An Uncertainty-Aware Ensemble Approach to Modeling Utility of Pseudolabels for Semisupervised Learning},
author = {Jiaqi Wu and Junbiao Pang and Qingming Huang},
year = {2026},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
doi = {10.1109/tnnls.2026.3696935},
url = {https://doi.org/10.1109/tnnls.2026.3696935}
}RIS
TY - JOUR TI - An Uncertainty-Aware Ensemble Approach to Modeling Utility of Pseudolabels for Semisupervised Learning AU - Jiaqi Wu AU - Junbiao Pang AU - Qingming Huang PY - 2026 JO - IEEE Transactions on Neural Networks and Learning Systems DO - 10.1109/tnnls.2026.3696935 UR - https://doi.org/10.1109/tnnls.2026.3696935 ER -
APA
Wu, J., Pang, J., & Huang, Q. (2026). An Uncertainty-Aware Ensemble Approach to Modeling Utility of Pseudolabels for Semisupervised Learning. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2026.3696935
Source records
- crossref · retrieved 2026-11-10T14:53:31.945Z