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 *

179 related articles for article (PubMed ID: 32092107)

  • 1. Pre-Synaptic Pool Modification (PSPM): A supervised learning procedure for recurrent spiking neural networks.
    Bagley BA; Bordelon B; Moseley B; Wessel R
    PLoS One; 2020; 15(2):e0229083. PubMed ID: 32092107
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A supervised multi-spike learning algorithm based on gradient descent for spiking neural networks.
    Xu Y; Zeng X; Han L; Yang J
    Neural Netw; 2013 Jul; 43():99-113. PubMed ID: 23500504
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. An online supervised learning method based on gradient descent for spiking neurons.
    Xu Y; Yang J; Zhong S
    Neural Netw; 2017 Sep; 93():7-20. PubMed ID: 28525811
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Supervised Learning in Multilayer Spiking Neural Networks With Spike Temporal Error Backpropagation.
    Luo X; Qu H; Wang Y; Yi Z; Zhang J; Zhang M
    IEEE Trans Neural Netw Learn Syst; 2023 Dec; 34(12):10141-10153. PubMed ID: 35436200
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Scalable Weight-Free Learning Algorithm for Regulatory Control of Cell Activity in Spiking Neuronal Networks.
    Zhang X; Foderaro G; Henriquez C; Ferrari S
    Int J Neural Syst; 2018 Mar; 28(2):1750015. PubMed ID: 28270025
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A biologically plausible supervised learning method for spiking neural networks using the symmetric STDP rule.
    Hao Y; Huang X; Dong M; Xu B
    Neural Netw; 2020 Jan; 121():387-395. PubMed ID: 31593843
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. An optimal time interval of input spikes involved in synaptic adjustment of spike sequence learning.
    Xu Y; Yang J; Zeng X
    Neural Netw; 2019 Aug; 116():11-24. PubMed ID: 30986723
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Learning to represent signals spike by spike.
    Brendel W; Bourdoukan R; Vertechi P; Machens CK; Denève S
    PLoS Comput Biol; 2020 Mar; 16(3):e1007692. PubMed ID: 32176682
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Supervised Learning Algorithm for Multilayer Spiking Neural Networks with Long-Term Memory Spike Response Model.
    Lin X; Zhang M; Wang X
    Comput Intell Neurosci; 2021; 2021():8592824. PubMed ID: 34868299
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. SpiFoG: an efficient supervised learning algorithm for the network of spiking neurons.
    Hussain I; Thounaojam DM
    Sci Rep; 2020 Aug; 10(1):13122. PubMed ID: 32753645
    [TBL] [Abstract][Full Text] [Related]  

  • 15. SPIDE: A purely spike-based method for training feedback spiking neural networks.
    Xiao M; Meng Q; Zhang Z; Wang Y; Lin Z
    Neural Netw; 2023 Apr; 161():9-24. PubMed ID: 36736003
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Robust spike-train learning in spike-event based weight update.
    Shrestha SB; Song Q
    Neural Netw; 2017 Dec; 96():33-46. PubMed ID: 28957730
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.
    Gardner B; Grüning A
    PLoS One; 2016; 11(8):e0161335. PubMed ID: 27532262
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains.
    Donner C; Bartram J; Hornauer P; Kim T; Roqueiro D; Hierlemann A; Obozinski G; Schröter M
    PLoS Comput Biol; 2024 Apr; 20(4):e1011964. PubMed ID: 38683881
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. II. Input selectivity--symmetry breaking.
    Gilson M; Burkitt AN; Grayden DB; Thomas DA; van Hemmen JL
    Biol Cybern; 2009 Aug; 101(2):103-14. PubMed ID: 19536559
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A Highly Effective and Robust Membrane Potential-Driven Supervised Learning Method for Spiking Neurons.
    Zhang M; Qu H; Belatreche A; Chen Y; Yi Z
    IEEE Trans Neural Netw Learn Syst; 2019 Jan; 30(1):123-137. PubMed ID: 29993588
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.