Variational Inference for De Finetti Logic
Summary: Introduces De Finetti Logic, a relational-constraint formalism for Gamma probabilistic databases grounded in Polya-urn exchangeability. Automatically synthesizes knowledge-compiled variational inference, yielding scalable, fast-converging posteriors competitive with Gibbs sampling and specialized methods. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Sami Hadouaj (University of Michigan-Dearborn)
- 2. Ouael Ben Amara (University of Michigan-Dearborn)
- 3. Niccolò Meneghetti (University of Michigan-Dearborn)
BibTeX Citation
@inproceedings{hadouaj_sigmod26,
title = {{Variational Inference for De Finetti Logic}},
author = {Hadouaj, Sami and Amara, Ouael Ben and Meneghetti, Niccolò},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802114},
url = {https://dl.acm.org/doi/10.1145/3802114},
year = {2026}
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Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 14 | MonetDB/X100: Hyper-Pipelining Query Execution | 2005 | CIDR | 0.00064031282 |
| 1,009 | Simulation of Database-Valued Markov Chains Using SimSQL | 2013 | SIGMOD | 0.00012539827 |
| 1,814 | ProvSQL: Provenance and Probability Management in PostgreSQL | 2018 | VLDB | 9.5800565e-05 |
| 2,400 | Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning | 2019 | VLDB | 8.5213814e-05 |
| 5,340 | Approximate Lifted Inference with Probabilistic Databases | 2015 | VLDB | 6.1731278e-05 |
| 6,129 | Generative Datalog with Continuous Distributions | 2020 | PODS | 5.8783975e-05 |
| 8,886 | FastPDB: Towards Bag-Probabilistic Queries at Interactive Speeds | 2025 | SIGMOD | 5.2559789e-05 |
| 11,532 | StarfishDB: a Query Execution Engine for Relational Probabilistic Programming | 2024 | SIGMOD | 4.9793485e-05 |
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