BayesDB: A probabilistic programming system for querying the probable
implications of data

BayesDB: A probabilistic programming system for querying the probable implications of data

15 December 2015

Vikash K. Mansinghka

Pat Shafto

Baxter S. Eaves

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Papers citing "BayesDB: A probabilistic programming system for querying the probable implications of data"

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Title
Automating Data Science: Prospects and Challenges Tijl De Bie Luc de Raedt José Hernández-Orallo Holger H. Hoos Padhraic Smyth C. Williams 114 38 0 12 May 2021
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming Alexander K. Lew Monica Agrawal David Sontag Vikash K. Mansinghka 134 28 0 23 Jul 2020
Minority Class Oversampling for Tabular Data with Deep Generative Models R. Camino Christian A. Hammerschmidt R. State 51 2 0 07 May 2020
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs Sungsoo Ray Hong Jessica Hullman E. Bertini HAI 87 195 0 23 Apr 2020
Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic Maria I. Gorinova Andrew D. Gordon Charles Sutton 77 24 0 02 Nov 2018
An Introduction to Probabilistic Programming Jan-Willem van de Meent Brooks Paige Hongseok Yang Frank Wood GP 88 200 0 27 Sep 2018
Database Learning: Toward a Database that Becomes Smarter Every Time Yongjoo Park Ahmad S. Tajik Michael Cafarella Barzan Mozafari 48 75 0 16 Mar 2017
Encapsulating models and approximate inference programs in probabilistic modules Marco F. Cusumano-Towner Vikash K. Mansinghka TPM 19 2 0 14 Dec 2016
Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes Feras A. Saad Vikash K. Mansinghka 50 14 0 05 Nov 2016