Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Tomasz Rybotycki"'
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
We analyze the results of the test of π/2 qubit rotations on a public quantum computer provided by IBM. We measure a single qubit rotated by π/2 about a random axis, and we accumulate vast statistics of the results. The test performed on different
Externí odkaz:
https://doaj.org/article/b1d944670c3c4d4a9827cd359156e427
Autor:
Gregory Morse, Tomasz Rybotycki, Ágoston Kaposi, Zoltán Kolarovszki, Uroš Stojčić, Tamás Kozsik, Oskar Mencer, Michał Oszmaniec, Zoltán Zimborás, Péter Rakyta
Publikováno v:
New Journal of Physics, Vol 26, Iss 3, p 033033 (2024)
Boson sampling (BS) is viewed to be an accessible quantum computing paradigm to demonstrate computational advantage compared to classical computers. In this context, the evolution of permanent calculation algorithms attracts a significant attention a
Externí odkaz:
https://doaj.org/article/ed6fb6acebf04277bad615286050d752
Autor:
Tomasz Rybotycki, Piotr Kulczycki
Publikováno v:
Computational Science – ICCS 2021 ISBN: 9783030779795
ICCS (6)
ICCS (6)
Recent growth in interest concerning streaming data has been forced by the expansion of systems successively providing current measurements and information, which enables their ongoing, consecutive analysis. The subject of this research is the determ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cdb6146d414fcd41d26fadf95e71a8c
https://doi.org/10.1007/978-3-030-77980-1_43
https://doi.org/10.1007/978-3-030-77980-1_43
Autor:
Tomasz Rybotycki
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030180577
The subject of this work is applying the artificial neural network (ANN) taught using two metaheuristics - the firefly algorithm (FA) and properly prepared evolutionary algorithm (EA) - to find the approximate solution of the Wessinger’s equation,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c15a791df64827f1d8b39da99f625772
https://doi.org/10.1007/978-3-030-18058-4_11
https://doi.org/10.1007/978-3-030-18058-4_11
Publikováno v:
Schedae Informaticae.
In this work the subject of the application of clustering as a knowledge extraction method from real-world data is discussed. The authors analyze an influence of different clustering parameters on the quality of the created structure of rules cluster
Publikováno v:
Computational Collective Intelligence ISBN: 9783319670768
ICCCI (2)
ICCCI (2)
This paper introduces the methodology of domain knowledge exploration in so called rule-based knowledge bases from the medical perspective, but it could easily by transformed into any other domain. The article presents the description of the CluVis s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18463bd9cc5869e0b082f2ae2e9cfcea
https://doi.org/10.1007/978-3-319-67077-5_15
https://doi.org/10.1007/978-3-319-67077-5_15
Publikováno v:
Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation ISBN: 9783319582733
BDAS
BDAS
In this work the subject of the application of clustering as a knowledge extraction method from real-world data is discussed. The authors analyze the influence of different clustering parameters on the efficiency of the knowledge mining process for r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25d4ae5b497e841617773810a4b1d9f3
https://doi.org/10.1007/978-3-319-58274-0_6
https://doi.org/10.1007/978-3-319-58274-0_6
Publikováno v:
Computational Collective Intelligence ISBN: 9783319452456
ICCCI (2)
ICCCI (2)
In this work, the topic of applying clustering as a knowledge extraction method from real-world data is discussed. The authors propose hierarchical clustering and treemap visualization techniques for knowledge base representation in the context of me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55540241e706558442b4088ad87fba87
https://doi.org/10.1007/978-3-319-45246-3_45
https://doi.org/10.1007/978-3-319-45246-3_45