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- 1.0537236 - ÚGN 2021 RIV CH eng C - Conference Paper (international conference)
Domesová, Simona
The use of radial basis function surrogate models for sampling process acceleration in Bayesian inversio.
Lecture Notes in Electrical Engineering. Vol. 554. Cham: Springer Nature Switzerland AG, 2020 - (Zelinka, I.; Brandstetter, P.; Trong Dao, T.; Hoang Duy, V.; Kim, S.), s. 228-238. ISBN 978-3-030-14906-2. ISSN 1876-1100. E-ISSN 1876-1119.
[International Conference on Advanced Engineering Theory and Applications 2018 /5./. Ostrava (CZ), 11.11.2018-13.11.2018]
R&D Projects: GA MŠMT LQ1602
Institutional support: RVO:68145535
Keywords : Bayesian inversion * Metropolis-Hastings * radial basis functions * surrogate model * uncertainty quantification
OECD category: Applied mathematics
https://link.springer.com/chapter/10.1007%2F978-3-030-14907-9_23
Permanent Link: http://hdl.handle.net/11104/0314976File Download Size Commentary Version Access UGN_0537236.pdf 1 528.6 KB Author’s postprint require - 2.0452414 - ASÚ 2016 RIV NL eng J - Journal Article
Bucha, B. - Bezděk, Aleš - Sebera, Josef - Janak, J.
Global and Regional Gravity Field Determination from GOCE Kinematic Orbit by Means of Spherical Radial Basis Functions.
Surveys in Geophysics. Roč. 36, č. 6 (2015), s. 773-801. ISSN 0169-3298. E-ISSN 1573-0956
R&D Projects: GA ČR GA13-36843S
Grant - others:SAV(SK) VEGA 1/0954/15
Institutional support: RVO:67985815
Keywords : spherical radial basis functions * spherical harmonics * geopotential
Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics
Impact factor: 3.622, year: 2015
Permanent Link: http://hdl.handle.net/11104/0253465 - 3.0404255 - UIVT-O 20030112 RIV US eng J - Journal Article
Šíma, Jiří - Orponen, P.
General-Purpose Computation with Neural Networks: A Survey of Complexity Theoretic Results.
Neural Computation. Roč. 15, č. 12 (2003), s. 2727-2778. ISSN 0899-7667. E-ISSN 1530-888X
R&D Projects: GA AV ČR IAB2030007; GA ČR GA201/02/1456
Institutional research plan: AV0Z1030915
Keywords : computational power * computational complexity * perceptrons * radial basis functions * spiking neurons * feedforward networks * reccurent networks * probabilistic computation * analog computation
Subject RIV: BA - General Mathematics
Impact factor: 2.747, year: 2003
Permanent Link: http://hdl.handle.net/11104/0124518File Download Size Commentary Version Access 0404255_tutorial.pdf 0 870.7 KB Other open-access 0404255.pdf 0 1 MB Author´s preprint open-access - 4.0404164 - UIVT-O 20010033 RIV AT eng C - Conference Paper (international conference)
Šíma, Jiří
The Computational Capabilities of Neural Networks.
Artificial Neural Nets and Genetic Algorithms. Proceedings of the International conference. Wien: Springer, 2001 - (Kůrková, V.; Steele, N.; Neruda, R.; Kárný, M.), s. 22-26. ISBN 3-211-83651-9.
[ICANNGA'2001 /5./. Praha (CZ), 22.04.2001-25.04.2001]
R&D Projects: GA MŠMT LN00A056
Keywords : computational power * computational complexity * perceptrons * radial basis functions * spiking neurons * probabilistic computation * analog computation
Subject RIV: BA - General Mathematics
https://link.springer.com/book/10.1007/978-3-7091-6230-9#toc
Permanent Link: http://hdl.handle.net/11104/0124431File Download Size Commentary Version Access 0404164.pdf 3 2.5 MB Author´s preprint open-access - 5.0402896 - UIVT-O 960206 CZ eng V - Research Report
Kůrková, Věra
Trade-off Between the Size of Weights and the Number of Hidden Units in Feedforward Networks.
Prague: ICS AS CR, 1996. 17 s. Technical Report, V-695.
R&D Projects: GA AV ČR IAA2030602; GA ČR GA201/96/0917
Keywords : approximation of functions * one-hidden-layer neural networks * sigmodial perceptrons * radial-basis-functions
Permanent Link: http://hdl.handle.net/11104/0123270File Download Size Commentary Version Access v695-96.pdf 13 249.8 KB Other open-access - 6.0331007 - ÚI 2010 RIV US eng C - Conference Paper (international conference)
Neruda, Roman - Slušný, Stanislav - Vidnerová, Petra
Performance Comparison of Relational Reinforcement Learning and RBF Neural Networks for Small Mobile Robots.
[Srovnání efektivity relačního posilovaného učení a RBF sítí pro malé mobilní roboty.]
Proceedings of Second International Conference on Future Generation Communication and Networking Symposia. Los Alamitos: IEEE Computer Society, 2008, s. 29-32. ISBN 978-1-4244-3430-5.
[CA 2008. International Symposium on Control and Automation. Sanya (CN), 13.12.2008-15.12.2008]
Grant - others:GA UK(CZ) 257367/2007
Institutional research plan: CEZ:AV0Z10300504
Keywords : neural networks * radial basis functions * reinforcement learning
Subject RIV: IN - Informatics, Computer Science
Permanent Link: http://hdl.handle.net/11104/0007351 - 7.0031806 - UIVT-O 336128 RIV FR eng C - Conference Paper (international conference)
Neruda, M. - Neruda, Roman - Kudová, Petra
Forecasting Runoff with Artificial Neural Networks.
[Předpovědi odtoků pomocí umělých neuronových sítí.]
Progress in Surface and Subsurface Water Studies at Plot and Small Basin Scale. Paris: UNESCO, 2005 - (Maraga, F.), s. 65-69
[ERB 2004. Euromediterranean Network of Experimental and Representative Basins /10./. Turin (IT), 13.10.2004-17.10.2004]
R&D Projects: GA ČR(CZ) GA201/02/0428
Institutional research plan: CEZ:AV0Z10300504
Keywords : artificial neural networks * rainfall-runoff modelling * multilayer perceptron * Radial Basis Functions (RBF)
Subject RIV: BA - General Mathematics
Permanent Link: http://hdl.handle.net/11104/0132452