2 citations · 2 across the 3 of their papers we have counts for
4 papers
Approach of variable clustering and compression for learning large Bayesian networks
Anna V. Bubnova
This paper describes a new approach for learning structures of large Bayesian networks based on blocks resulting from feature space clustering. This clustering is obtained using no…
Oil reservoir recovery factor assessment using Bayesian networks based on advanced approaches to analogues clustering
Petr Andriushchenko, Irina Deeva, Anna Bubnova +4
The work focuses on the modelling and imputation of oil and gas reservoirs parameters, specifically, the problem of predicting the oil recovery factor (RF) using Bayesian networks…
MIxBN: library for learning Bayesian networks from mixed data
Anna V. Bubnova, Irina Deeva, Anna V. Kalyuzhnaya
This paper describes a new library for learning Bayesian networks from data containing discrete and continuous variables (mixed data). In addition to the classical learning methods…
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks
Irina Deeva, Anna Bubnova, Petr Andriushchenko +4
In this paper, a multipurpose Bayesian-based method for data analysis, causal inference and prediction in the sphere of oil and gas reservoir development is considered. This allows…