BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

283 related articles for article (PubMed ID: 26446303)

  • 1. A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron.
    Ortín S; Soriano MC; Pesquera L; Brunner D; San-Martín D; Fischer I; Mirasso CR; Gutiérrez JM
    Sci Rep; 2015 Oct; 5():14945. PubMed ID: 26446303
    [TBL] [Abstract][Full Text] [Related]  

  • 2. High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.
    Rosselló JL; Alomar ML; Morro A; Oliver A; Canals V
    Int J Neural Syst; 2016 Aug; 26(5):1550036. PubMed ID: 26906454
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Recent advances in physical reservoir computing: A review.
    Tanaka G; Yamane T; Héroux JB; Nakane R; Kanazawa N; Takeda S; Numata H; Nakano D; Hirose A
    Neural Netw; 2019 Jul; 115():100-123. PubMed ID: 30981085
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality.
    Grigoryeva L; Henriques J; Larger L; Ortega JP
    Neural Netw; 2014 Jul; 55():59-71. PubMed ID: 24732236
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Recurrent kernel machines: computing with infinite echo state networks.
    Hermans M; Schrauwen B
    Neural Comput; 2012 Jan; 24(1):104-33. PubMed ID: 21851278
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Distributed computing methodology for training neural networks in an image-guided diagnostic application.
    Plagianakos VP; Magoulas GD; Vrahatis MN
    Comput Methods Programs Biomed; 2006 Mar; 81(3):228-35. PubMed ID: 16476503
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Reservoir computing and extreme learning machines for non-linear time-series data analysis.
    Butcher JB; Verstraeten D; Schrauwen B; Day CR; Haycock PW
    Neural Netw; 2013 Feb; 38():76-89. PubMed ID: 23275138
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Real-time computing without stable states: a new framework for neural computation based on perturbations.
    Maass W; Natschläger T; Markram H
    Neural Comput; 2002 Nov; 14(11):2531-60. PubMed ID: 12433288
    [TBL] [Abstract][Full Text] [Related]  

  • 9. FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.
    Alomar ML; Canals V; Perez-Mora N; Martínez-Moll V; Rosselló JL
    Comput Intell Neurosci; 2016; 2016():3917892. PubMed ID: 26880876
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The combination of circle topology and leaky integrator neurons remarkably improves the performance of echo state network on time series prediction.
    Xue F; Li Q; Li X
    PLoS One; 2017; 12(7):e0181816. PubMed ID: 28759581
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Delay-based reservoir computing: noise effects in a combined analog and digital implementation.
    Soriano MC; Ortín S; Keuninckx L; Appeltant L; Danckaert J; Pesquera L; van der Sande G
    IEEE Trans Neural Netw Learn Syst; 2015 Feb; 26(2):388-93. PubMed ID: 25608295
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Photonic nonlinear transient computing with multiple-delay wavelength dynamics.
    Martinenghi R; Rybalko S; Jacquot M; Chembo YK; Larger L
    Phys Rev Lett; 2012 Jun; 108(24):244101. PubMed ID: 23004274
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An experimental unification of reservoir computing methods.
    Verstraeten D; Schrauwen B; D'Haene M; Stroobandt D
    Neural Netw; 2007 Apr; 20(3):391-403. PubMed ID: 17517492
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning based on reservoir computing with time-delayed optoelectronic and photonic systems.
    Chembo YK
    Chaos; 2020 Jan; 30(1):013111. PubMed ID: 32013503
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Rotating neurons for all-analog implementation of cyclic reservoir computing.
    Liang X; Zhong Y; Tang J; Liu Z; Yao P; Sun K; Zhang Q; Gao B; Heidari H; Qian H; Wu H
    Nat Commun; 2022 Mar; 13(1):1549. PubMed ID: 35322037
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A forecast-based STDP rule suitable for neuromorphic implementation.
    Davies S; Galluppi F; Rast AD; Furber SB
    Neural Netw; 2012 Aug; 32():3-14. PubMed ID: 22386500
    [TBL] [Abstract][Full Text] [Related]  

  • 17. VLSI circuits implementing computational models of neocortical circuits.
    Wijekoon JH; Dudek P
    J Neurosci Methods; 2012 Sep; 210(1):93-109. PubMed ID: 22342970
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Nonlinear regularization path for quadratic loss support vector machines.
    Karasuyama M; Takeuchi I
    IEEE Trans Neural Netw; 2011 Oct; 22(10):1613-25. PubMed ID: 21880570
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Optimization and applications of echo state networks with leaky-integrator neurons.
    Jaeger H; Lukosevicius M; Popovici D; Siewert U
    Neural Netw; 2007 Apr; 20(3):335-52. PubMed ID: 17517495
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Learning to decode human emotions with Echo State Networks.
    Bozhkov L; Koprinkova-Hristova P; Georgieva P
    Neural Netw; 2016 Jun; 78():112-9. PubMed ID: 26422421
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.