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ImputeVIS: An Interactive Evaluator to Benchmark Imputation Techniques for Time Series Data

Summary: ImputeVIS is an interactive, open-source dashboard for benchmarking time-series imputation under configurable consecutive-missing-block scenarios. It combines imputation-focused profiling, composable corruption patterns, explainable comparisons, and AutoML-based parameter optimization. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13837
Venue
VLDB
Year
2024
Pagerank
5.2755515e-05
Overall Rank
9,390 | 35.58%
DOI
10.14778/3685800.3685867

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{khayati_vldb24,
        title = {{ImputeVIS: An Interactive Evaluator to Benchmark Imputation Techniques for Time Series Data}},
        author = {Khayati, Mourad and Nater, Quentin and Pasquier, Jacques},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {12},
        pages = {4329--4332},
        doi = {10.14778/3685800.3685867},
        url = {https://doi.org/10.14778/3685800.3685867},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
10,981 DIM-SUM: Dynamic Imputation for Smart Utility Management 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

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

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