Vladimir Puzyrev

Orcid: 0000-0002-0264-6126

According to our database1, Vladimir Puzyrev authored at least 15 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Deep Learning for Nonlinear Characterization of Electrostatic Vibrating Beam MEMS.
Int. J. Bifurc. Chaos, December, 2023

Deep semi-supervised learning using generative adversarial networks for automated seismic facies classification of mass transport complex.
Comput. Geosci., November, 2023

2022
AnalyZr: A Python application for zircon grain image segmentation and shape analysis.
Comput. Geosci., 2022

2021
Inversion of 1D frequency- and time-domain electromagnetic data with convolutional neural networks.
Comput. Geosci., 2021

2020
Efficient mass and stiffness matrix assembly via weighted Gaussian quadrature rules for B-splines.
J. Comput. Appl. Math., 2020

Unsupervised seismic facies classification using deep convolutional autoencoder.
CoRR, 2020

2019
<i>pyROM</i>: A computational framework for reduced order modeling.
J. Comput. Sci., 2019

Isogeometric spectral approximation for elliptic differential operators.
J. Comput. Sci., 2019

Dispersion optimized quadratures for isogeometric analysis.
J. Comput. Appl. Math., 2019

Deep convolutional autoencoder for cryptocurrency market analysis.
CoRR, 2019

2018
Deep learning electromagnetic inversion with convolutional neural networks.
CoRR, 2018

2017
Quadrature blending for isogeometric analysis.
Proceedings of the International Conference on Computational Science, 2017

2016
Evaluation of parallel direct sparse linear solvers in electromagnetic geophysical problems.
Comput. Geosci., 2016

A Parallel Tool for Numerical Approximation of 3D Electromagnetic Surveys in Geophysics.
Computación y Sistemas, 2016

Dispersion-optimized quadrature rules for isogeometric analysis: modified inner products, their dispersion properties, and optimally blended schemes.
CoRR, 2016


  Loading...