NeuroCard: One Cardinality Estimator for All Tables
Summary: NeuroCard uses a single neural density estimator over the database to model join cardinalities, with no independence assumptions. Join sampling and autoregressive modeling achieve state-of-the-art accuracy; scalable to dozens of tables and compact to train. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zongheng Yang (University of California Berkeley)
- 2. Amog Kamsetty (University of California Berkeley)
- 3. Sifei Luan (University of California Berkeley)
- 4. Eric Liang (University of California Berkeley)
- 5. Yan Duan (Covariant)
- 6. Xi Chen (Covariant)
- 7. Ion Stoica (University of California Berkeley)
BibTeX Citation
@article{yang_vldb21,
title = {{NeuroCard: One Cardinality Estimator for All Tables}},
author = {Yang, Zongheng and Kamsetty, Amog and Luan, Sifei and Liang, Eric and Duan, Yan and Chen, Xi and Stoica, Ion},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {1},
pages = {61--73},
doi = {10.14778/3421424.3421432},
url = {https://doi.org/10.14778/3421424.3421432},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 28 of 28 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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