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Efficient and Portable Einstein Summation in SQL

Summary: Einstein summation for tensors is implemented in SQL with four mapping rules and a CTE-based decomposition, yielding portable, efficient expressions. Demonstrates use cases in triplestore queries, SAT solving, graphical-model inference, and quantum circuit simulation, and notes engine-dependent performance as a key SQL research challenge. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6624
Venue
SIGMOD
Year
2023
Pagerank
6.0953447e-05
Overall Rank
4,548 | 68.37%
DOI
10.1145/3589266

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Showing 11 of 11 cited papers.

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

Rank Cited Paper Year Venue Pagerank
51 Including Group-By in Query Optimization 1994 VLDB 0.00067123727
140 The MADlib Analytics Library or MAD Skills, the SQL 2012 VLDB 0.00042270404
168 MAD Skills: New Analysis Practices for Big Data 2009 VLDB 0.00038946305
185 DuckDB: an Embeddable Analytical Database 2019 SIGMOD 0.00036538405
658 Towards a Unified Architecture for in-RDBMS Analytics 2012 SIGMOD 0.00018506577
1,158 Simulation of Database-Valued Markov Chains Using SimSQL 2013 SIGMOD 0.0001361064
3,648 One WITH RECURSIVE is Worth Many GOTOs 2021 SIGMOD 6.8831123e-05
4,409 Declarative Recursive Computation on an RDBMS 2019 VLDB 6.2104034e-05
5,294 GLADE: Big Data Analytics Made Easy 2012 SIGMOD 5.5810654e-05
6,212 Snakes on a Plan: Compiling Python Functions into Plain SQL Queries 2022 SIGMOD 5.1552576e-05
6,990 Machine Learning, Linear Algebra, and More: Is SQL All You Need? 2022 CIDR 4.8704904e-05
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