These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

219 related articles for article (PubMed ID: 29531065)

  • 1. Blindfold learning of an accurate neural metric.
    Gardella C; Marre O; Mora T
    Proc Natl Acad Sci U S A; 2018 Mar; 115(13):3267-3272. PubMed ID: 29531065
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Spiking Neural Network System for Robust Sequence Recognition.
    Yu Q; Yan R; Tang H; Tan KC; Li H
    IEEE Trans Neural Netw Learn Syst; 2016 Mar; 27(3):621-35. PubMed ID: 25879976
    [TBL] [Abstract][Full Text] [Related]  

  • 3. The tempotron: a neuron that learns spike timing-based decisions.
    Gütig R; Sompolinsky H
    Nat Neurosci; 2006 Mar; 9(3):420-8. PubMed ID: 16474393
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Learning precisely timed spikes.
    Memmesheimer RM; Rubin R; Olveczky BP; Sompolinsky H
    Neuron; 2014 May; 82(4):925-38. PubMed ID: 24768299
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Neural decoding with kernel-based metric learning.
    Brockmeier AJ; Choi JS; Kriminger EG; Francis JT; Principe JC
    Neural Comput; 2014 Jun; 26(6):1080-107. PubMed ID: 24684447
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Supervised learning in spiking neural networks with ReSuMe: sequence learning, classification, and spike shifting.
    Ponulak F; Kasiński A
    Neural Comput; 2010 Feb; 22(2):467-510. PubMed ID: 19842989
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Span: spike pattern association neuron for learning spatio-temporal spike patterns.
    Mohemmed A; Schliebs S; Matsuda S; Kasabov N
    Int J Neural Syst; 2012 Aug; 22(4):1250012. PubMed ID: 22830962
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Supervised learning with decision margins in pools of spiking neurons.
    Le Mouel C; Harris KD; Yger P
    J Comput Neurosci; 2014 Oct; 37(2):333-44. PubMed ID: 24862859
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Learning probabilistic neural representations with randomly connected circuits.
    Maoz O; Tkačik G; Esteki MS; Kiani R; Schneidman E
    Proc Natl Acad Sci U S A; 2020 Oct; 117(40):25066-25073. PubMed ID: 32948691
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A solution to the learning dilemma for recurrent networks of spiking neurons.
    Bellec G; Scherr F; Subramoney A; Hajek E; Salaj D; Legenstein R; Maass W
    Nat Commun; 2020 Jul; 11(1):3625. PubMed ID: 32681001
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Introduction to spiking neural networks: Information processing, learning and applications.
    Ponulak F; Kasinski A
    Acta Neurobiol Exp (Wars); 2011; 71(4):409-33. PubMed ID: 22237491
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Neural heterogeneity promotes robust learning.
    Perez-Nieves N; Leung VCH; Dragotti PL; Goodman DFM
    Nat Commun; 2021 Oct; 12(1):5791. PubMed ID: 34608134
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Reading-out task variables as a low-dimensional reconstruction of neural spike trains in single trials.
    Koren V; Andrei AR; Hu M; Dragoi V; Obermayer K
    PLoS One; 2019; 14(10):e0222649. PubMed ID: 31622346
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.
    Onken A; Liu JK; Karunasekara PP; Delis I; Gollisch T; Panzeri S
    PLoS Comput Biol; 2016 Nov; 12(11):e1005189. PubMed ID: 27814363
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Synaptic dynamics: linear model and adaptation algorithm.
    Yousefi A; Dibazar AA; Berger TW
    Neural Netw; 2014 Aug; 56():49-68. PubMed ID: 24867390
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Learning beyond finite memory in recurrent networks of spiking neurons.
    Tino P; Mills AJ
    Neural Comput; 2006 Mar; 18(3):591-613. PubMed ID: 16483409
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Bayesian spiking neurons II: learning.
    Deneve S
    Neural Comput; 2008 Jan; 20(1):118-45. PubMed ID: 18045003
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Learning in neural networks by reinforcement of irregular spiking.
    Xie X; Seung HS
    Phys Rev E Stat Nonlin Soft Matter Phys; 2004 Apr; 69(4 Pt 1):041909. PubMed ID: 15169045
    [TBL] [Abstract][Full Text] [Related]  

  • 19. From space to time: Spatial inhomogeneities lead to the emergence of spatiotemporal sequences in spiking neuronal networks.
    Spreizer S; Aertsen A; Kumar A
    PLoS Comput Biol; 2019 Oct; 15(10):e1007432. PubMed ID: 31652259
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Sparse Temporal Encoding of Visual Features for Robust Object Recognition by Spiking Neurons.
    Zheng Y; Li S; Yan R; Tang H; Tan KC
    IEEE Trans Neural Netw Learn Syst; 2018 Dec; 29(12):5823-5833. PubMed ID: 29994102
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.