2 citations · 2 across the 3 of their papers we have counts for
4 papers
BigBraveBN: algorithm of structural learning for bayesian networks with a large number of nodes
Yury Kaminsky, Irina Deeva
Learning a Bayesian network is an NP-hard problem and with an increase in the number of nodes, classical algorithms for learning the structure of Bayesian networks become inefficie…
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…