BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

539 related articles for article (PubMed ID: 23800216)

  • 1. Where do features come from?
    Hinton G
    Cogn Sci; 2014 Aug; 38(6):1078-101. PubMed ID: 23800216
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An efficient learning procedure for deep Boltzmann machines.
    Salakhutdinov R; Hinton G
    Neural Comput; 2012 Aug; 24(8):1967-2006. PubMed ID: 22509963
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Representational power of restricted boltzmann machines and deep belief networks.
    Le Roux N; Bengio Y
    Neural Comput; 2008 Jun; 20(6):1631-49. PubMed ID: 18254699
    [TBL] [Abstract][Full Text] [Related]  

  • 4. On the equivalence of Hopfield networks and Boltzmann Machines.
    Barra A; Bernacchia A; Santucci E; Contucci P
    Neural Netw; 2012 Oct; 34():1-9. PubMed ID: 22784924
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Learning Orthographic Structure With Sequential Generative Neural Networks.
    Testolin A; Stoianov I; Sperduti A; Zorzi M
    Cogn Sci; 2016 Apr; 40(3):579-606. PubMed ID: 26073971
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Expected energy-based restricted Boltzmann machine for classification.
    Elfwing S; Uchibe E; Doya K
    Neural Netw; 2015 Apr; 64():29-38. PubMed ID: 25318375
    [TBL] [Abstract][Full Text] [Related]  

  • 7. An improvement of extreme learning machine for compact single-hidden-layer feedforward neural networks.
    Huynh HT; Won Y; Kim JJ
    Int J Neural Syst; 2008 Oct; 18(5):433-41. PubMed ID: 18991365
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Accelerating deep learning with memcomputing.
    Manukian H; Traversa FL; Di Ventra M
    Neural Netw; 2019 Feb; 110():1-7. PubMed ID: 30458316
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Dynamical analysis of contrastive divergence learning: Restricted Boltzmann machines with Gaussian visible units.
    Karakida R; Okada M; Amari S
    Neural Netw; 2016 Jul; 79():78-87. PubMed ID: 27131468
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A fast learning algorithm for deep belief nets.
    Hinton GE; Osindero S; Teh YW
    Neural Comput; 2006 Jul; 18(7):1527-54. PubMed ID: 16764513
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Learning multiple layers of representation.
    Hinton GE
    Trends Cogn Sci; 2007 Oct; 11(10):428-34. PubMed ID: 17921042
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A learning rule for very simple universal approximators consisting of a single layer of perceptrons.
    Auer P; Burgsteiner H; Maass W
    Neural Netw; 2008 Jun; 21(5):786-95. PubMed ID: 18249524
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Measuring the usefulness of hidden units in Boltzmann machines with mutual information.
    Berglund M; Raiko T; Cho K
    Neural Netw; 2015 Apr; 64():12-8. PubMed ID: 25318376
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Enhanced gradient for training restricted Boltzmann machines.
    Cho K; Raiko T; Ilin A
    Neural Comput; 2013 Mar; 25(3):805-31. PubMed ID: 23148412
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep neural mapping support vector machines.
    Li Y; Zhang T
    Neural Netw; 2017 Sep; 93():185-194. PubMed ID: 28646763
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Autoencoder and restricted Boltzmann machine for transfer learning in functional magnetic resonance imaging task classification.
    Hwang J; Lustig N; Jung M; Lee JH
    Heliyon; 2023 Jul; 9(7):e18086. PubMed ID: 37519689
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding.
    Testolin A; De Filippo De Grazia M; Zorzi M
    Front Comput Neurosci; 2017; 11():13. PubMed ID: 28377709
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Refinements of universal approximation results for deep belief networks and restricted Boltzmann machines.
    Montufar G; Ay N
    Neural Comput; 2011 May; 23(5):1306-19. PubMed ID: 21299421
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition.
    Kasabov N; Dhoble K; Nuntalid N; Indiveri G
    Neural Netw; 2013 May; 41():188-201. PubMed ID: 23340243
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Intelligent initialization of resource allocating RBF networks.
    Wallace M; Tsapatsoulis N; Kollias S
    Neural Netw; 2005 Mar; 18(2):117-22. PubMed ID: 15795110
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 27.