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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence / EAAI-20

Automatic Bayesian Density Analysis

February 1, 2023

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Authors

Antonio Vergari

Max-Planck Institute for Intelligent Systems


Alejandro Molina

TU Darmstadt


Robert Peharz

University of Cambridge


Zoubin Ghahramani

University of Cambridge


Kristian Kersting

TU Darmstadt


Isabel Valera

Max Planck Institute for Intelligence Systems


DOI:

10.1609/aaai.v33i01.33015207


Abstract:

Making sense of a dataset in an automatic and unsupervised fashion is a challenging problem in statistics and AI. Classical approaches for exploratory data analysis are usually not flexible enough to deal with the uncertainty inherent to real-world data: they are often restricted to fixed latent interaction models and homogeneous likelihoods; they are sensitive to missing, corrupt and anomalous data; moreover, their expressiveness generally comes at the price of intractable inference. As a result, supervision from statisticians is usually needed to find the right model for the data. However, since domain experts are not necessarily also experts in statistics, we propose Automatic Bayesian Density Analysis (ABDA) to make exploratory data analysis accessible at large. Specifically, ABDA allows for automatic and efficient missing value estimation, statistical data type and likelihood discovery, anomaly detection and dependency structure mining, on top of providing accurate density estimation. Extensive empirical evidence shows that ABDA is a suitable tool for automatic exploratory analysis of mixed continuous and discrete tabular data.

Topics: AAAI

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HOW TO CITE:

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera Automatic Bayesian Density Analysis Proceedings of the AAAI Conference on Artificial Intelligence (2019) 5207-5215.

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera Automatic Bayesian Density Analysis AAAI 2019, 5207-5215.

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera (2019). Automatic Bayesian Density Analysis. Proceedings of the AAAI Conference on Artificial Intelligence, 5207-5215.

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera. Automatic Bayesian Density Analysis. Proceedings of the AAAI Conference on Artificial Intelligence 2019 p.5207-5215.

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera. 2019. Automatic Bayesian Density Analysis. "Proceedings of the AAAI Conference on Artificial Intelligence". 5207-5215.

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera. (2019) "Automatic Bayesian Density Analysis", Proceedings of the AAAI Conference on Artificial Intelligence, p.5207-5215

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera, "Automatic Bayesian Density Analysis", AAAI, p.5207-5215, 2019.

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera. "Automatic Bayesian Density Analysis". Proceedings of the AAAI Conference on Artificial Intelligence, 2019, p.5207-5215.

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera. "Automatic Bayesian Density Analysis". Proceedings of the AAAI Conference on Artificial Intelligence, (2019): 5207-5215.

Antonio Vergari||Alejandro Molina||Robert Peharz||Zoubin Ghahramani||Kristian Kersting||Isabel Valera. Automatic Bayesian Density Analysis. AAAI[Internet]. 2019[cited 2023]; 5207-5215.


ISSN: 2374-3468


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