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 *

170 related articles for article (PubMed ID: 35622431)

  • 41. Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks.
    Triche A; Maida AS; Kumar A
    Neural Netw; 2022 Jul; 151():16-33. PubMed ID: 35367735
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Provenance of life: Chemical autonomous agents surviving through associative learning.
    Bartlett S; Louapre D
    Phys Rev E; 2022 Sep; 106(3-1):034401. PubMed ID: 36266823
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence.
    Abderrahmane N; Lemaire E; Miramond B
    Neural Netw; 2020 Jan; 121():366-386. PubMed ID: 31593842
    [TBL] [Abstract][Full Text] [Related]  

  • 44. A nonlinear neural network based on an analog DNA toehold mediated strand displacement reaction circuit.
    Zou C; Zhang Q; Zhou C; Cao W
    Nanoscale; 2022 May; 14(17):6585-6599. PubMed ID: 35421885
    [TBL] [Abstract][Full Text] [Related]  

  • 45. 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]  

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

  • 47. Anti-Hebbian learning in a non-linear neural network.
    Carlson A
    Biol Cybern; 1990; 64(2):171-6. PubMed ID: 2291904
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Integrating Non-spiking Interneurons in Spiking Neural Networks.
    Strohmer B; Stagsted RK; Manoonpong P; Larsen LB
    Front Neurosci; 2021; 15():633945. PubMed ID: 33746701
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Learning anticipation via spiking networks: application to navigation control.
    Arena P; Fortuna L; Frasca M; Patané L
    IEEE Trans Neural Netw; 2009 Feb; 20(2):202-16. PubMed ID: 19150797
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Supervised learning in spiking neural networks: A review of algorithms and evaluations.
    Wang X; Lin X; Dang X
    Neural Netw; 2020 May; 125():258-280. PubMed ID: 32146356
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.
    Sinapayen L; Masumori A; Ikegami T
    PLoS One; 2017; 12(2):e0170388. PubMed ID: 28158309
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Contrastive Similarity Matching for Supervised Learning.
    Qin S; Mudur N; Pehlevan C
    Neural Comput; 2021 Apr; 33(5):1300-1328. PubMed ID: 33617744
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks.
    Walter F; Röhrbein F; Knoll A
    Neural Netw; 2015 Dec; 72():152-67. PubMed ID: 26422422
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots.
    Cyr A; Thériault F
    Comput Intell Neurosci; 2019; 2019():8361369. PubMed ID: 31065256
    [TBL] [Abstract][Full Text] [Related]  

  • 55. A 0.086-mm
    Frenkel C; Lefebvre M; Legat JD; Bol D
    IEEE Trans Biomed Circuits Syst; 2019 Feb; 13(1):145-158. PubMed ID: 30418919
    [TBL] [Abstract][Full Text] [Related]  

  • 56. 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]  

  • 57. Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule.
    Beyeler M; Dutt ND; Krichmar JL
    Neural Netw; 2013 Dec; 48():109-24. PubMed ID: 23994510
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Post and pre-compensatory Hebbian learning for categorisation.
    Huyck CR; Mitchell IG
    Cogn Neurodyn; 2014 Aug; 8(4):299-311. PubMed ID: 25009672
    [TBL] [Abstract][Full Text] [Related]  

  • 59. A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis.
    Lipshutz D; Bahroun Y; Golkar S; Sengupta AM; Chklovskii DB
    Neural Comput; 2021 Aug; 33(9):2309-2352. PubMed ID: 34412114
    [TBL] [Abstract][Full Text] [Related]  

  • 60. A reinforcement learning framework for spiking networks with dynamic synapses.
    El-Laithy K; Bogdan M
    Comput Intell Neurosci; 2011; 2011():869348. PubMed ID: 22046180
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.