Bidirectional f-Divergence-Based Deep Generative Method for Imputing Missing Values in Time-Series Data

Wen-Shan Liu, Tong Si, Aldas Kriauciunas, Marcus Snell, Haijun Gong

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DOI: 10.3390/stats8010007
Published: 2025-01-14
Container: Stats
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/stats8010007,
  title = {Bidirectional f-Divergence-Based Deep Generative Method for Imputing Missing Values in Time-Series Data},
  author = {Wen-Shan Liu and Tong Si and Aldas Kriauciunas and Marcus Snell and Haijun Gong},
  year = {2025},
  journal = {Stats},
  doi = {10.3390/stats8010007},
  url = {https://doi.org/10.3390/stats8010007}
}

RIS

TY  - JOUR
TI  - Bidirectional f-Divergence-Based Deep Generative Method for Imputing Missing Values in Time-Series Data
AU  - Wen-Shan Liu
AU  - Tong Si
AU  - Aldas Kriauciunas
AU  - Marcus Snell
AU  - Haijun Gong
PY  - 2025
JO  - Stats
DO  - 10.3390/stats8010007
UR  - https://doi.org/10.3390/stats8010007
ER  -

APA

Liu, W., Si, T., Kriauciunas, A., Snell, M., & Gong, H. (2025). Bidirectional f-Divergence-Based Deep Generative Method for Imputing Missing Values in Time-Series Data. Stats. https://doi.org/10.3390/stats8010007

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crossref · retrieved 2026-09-26T19:07:19.968Z