Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Vadim Tulchinsky"'
Autor:
Ruslan Vdovychenko, Vadim Tulchinsky
Publikováno v:
Кібернетика та комп'ютерні технології, Iss 2, Pp 58-66 (2022)
Introduction. Sparse Distributed Memory (SDM) and Binary Sparse Distributed Representations (Binary Sparse Distributed Representations, BSDR), as two phenomenological approaches to biological memory modelling, have many similarities. The idea of ??th
Externí odkaz:
https://doaj.org/article/a49cd3fb565c46f2a4497a8bd11bae86
Autor:
Vadim Tulchinsky, Serhii Lavreniuk, Viacheslav Roganov, Petro Tulchinsky, Valerii Khalimendik
Publikováno v:
Кібернетика та комп'ютерні технології, Iss 1, Pp 74-82 (2020)
Introduction. In machine learning (ML) and artificial intelligence (AI) works, the emphasis is usually on the quality of classification or the accuracy of parameter estimation. If the focus is on performance, then it is also mainly about the performa
Externí odkaz:
https://doaj.org/article/793200cbc6604a5fa01219c396cc875a
Autor:
Ruslan Vdovychenko, Vadim Tulchinsky
Publikováno v:
Lecture Notes in Networks and Systems ISBN: 9783031160714
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bbbfe4f2ebec8aad10a34a8783551837
https://doi.org/10.1007/978-3-031-16072-1_5
https://doi.org/10.1007/978-3-031-16072-1_5
Autor:
Petro Tulchinsky, Valerii Khalimendik, Serhii Lavreniuk, Viacheslav Roganov, Vadim Tulchinsky
Publikováno v:
Кібернетика та комп'ютерні технології, Iss 1, Pp 74-82 (2020)
Introduction. In machine learning (ML) and artificial intelligence (AI) works, the emphasis is usually on the quality of classification or the accuracy of parameter estimation. If the focus is on performance, then it is also mainly about the performa
Autor:
Ruslan Vdovychenko, Vadim Tulchinsky
Publikováno v:
2022 7th International Conference on Machine Learning Technologies (ICMLT).
Publikováno v:
Day 2 Tue, October 27, 2020.
Nowadays, Machine Learning (ML) is actively used in geophysical prospecting including seismic exploration. This study focuses on the applicability and feasibility of Deep Learning for the inverse problem in seismic exploration that is the estimation
Publikováno v:
SPE Russian Petroleum Technology Conference.