DBScholar

Back to papers

Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series

Summary: A broad, uniform benchmark re-implements and evaluates 12 time-series missing-block imputation methods across 10 diverse sensor datasets. It exposes use-case-dependent strengths and weaknesses, recommends techniques, and identifies gaps for future algorithm development. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12461
Venue
VLDB
Year
2020
Pagerank
8.4401333e-05
Overall Rank
2,545 | 82.55%
DOI
10.14778/3377369.3377383

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{khayati_vldb20,
        title = {{Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series}},
        author = {Khayati, Mourad and Lerner, Alberto and Tymchenko, Zakhar and Cudré-Mauroux, Philippe},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {5},
        pages = {768--782},
        doi = {10.14778/3377369.3377383},
        url = {https://doi.org/10.14778/3377369.3377383},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 15 of 15 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers