103 citations · 112 across the 3 of their papers we have counts for
9 papers
Learning to Approximate Directional Fields Defined over 2D Planes
Maria Taktasheva, Albert Matveev, Alexey Artemov +1
Reconstruction of directional fields is a need in many geometry processing tasks, such as image tracing, extraction of 3D geometric features, and finding principal surface directio…
Topological Data Analysis of Time Series Data for B2B Customer Relationship Management
Rodrigo Rivera-Castro, Polina Pilyugina, Alexander Pletnev +3
Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure. Its use for time series data has been limited to the…
Rare Failure Prediction via Event Matching for Aerospace Applications
Evgeny Burnaev
In this paper, we consider a problem of failure prediction in the context of predictive maintenance applications. We present a new approach for rare failures prediction, based on a…
A Predictive Model for Steady-State Multiphase Pipe Flow: Machine Learning on Lab Data
Evgenii Kanin, Andrei Osiptsov, Albert Vainshtein +1
Engineering simulators used for steady-state multiphase pipe flows are commonly utilized to predict pressure drop. Such simulators are typically based on either empirical correlati…
Procedural Synthesis of Remote Sensing Images for Robust Change Detection with Neural Networks
Maria Kolos, Anton Marin, Alexey Artemov +1
Data-driven methods such as convolutional neural networks (CNNs) are known to deliver state-of-the-art performance on image recognition tasks when the training data are abundant. H…
Artificial Neural Network Surrogate Modeling of Oil Reservoir: a Case Study
Oleg Sudakov, Dmitri Koroteev, Boris Belozerov +1
We develop a data-driven model, introducing recent advances in machine learning to reservoir simulation. We use a conventional reservoir modeling tool to generate training set and…