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)
Showing 42 of 92 citing papers.
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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