Robust adversarial uncertainty quantification for deep learning fine-tuning.

Ahmed U, Lin JC

DOI: 10.1007/s11227-023-05087-5
Published: 2023
Container: The Journal of supercomputing
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.1007/s11227-023-05087-5,
  title = {Robust adversarial uncertainty quantification for deep learning fine-tuning.},
  author = {Ahmed U and Lin JC},
  year = {2023},
  journal = {The Journal of supercomputing},
  doi = {10.1007/s11227-023-05087-5},
  url = {https://doi.org/10.1007/s11227-023-05087-5}
}

RIS

TY  - JOUR
TI  - Robust adversarial uncertainty quantification for deep learning fine-tuning.
AU  - Ahmed U
AU  - Lin JC
PY  - 2023
JO  - The Journal of supercomputing
DO  - 10.1007/s11227-023-05087-5
UR  - https://doi.org/10.1007/s11227-023-05087-5
ER  -

APA

U, A., & JC, L. (2023). Robust adversarial uncertainty quantification for deep learning fine-tuning.. The Journal of supercomputing. https://doi.org/10.1007/s11227-023-05087-5

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pubmed · retrieved 2026-11-11T00:23:20.225Z