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 *

196 related articles for article (PubMed ID: 35082422)

  • 1. Deep physical neural networks trained with backpropagation.
    Wright LG; Onodera T; Stein MM; Wang T; Schachter DT; Hu Z; McMahon PL
    Nature; 2022 Jan; 601(7894):549-555. PubMed ID: 35082422
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep convolutional neural network and IoT technology for healthcare.
    Wassan S; Dongyan H; Suhail B; Jhanjhi NZ; Xiao G; Ahmed S; Murugesan RK
    Digit Health; 2024; 10():20552076231220123. PubMed ID: 38250147
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Backpropagation-free training of deep physical neural networks.
    Momeni A; Rahmani B; Malléjac M; Del Hougne P; Fleury R
    Science; 2023 Dec; 382(6676):1297-1303. PubMed ID: 37995209
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Experimentally realized in situ backpropagation for deep learning in photonic neural networks.
    Pai S; Sun Z; Hughes TW; Park T; Bartlett B; Williamson IAD; Minkov M; Milanizadeh M; Abebe N; Morichetti F; Melloni A; Fan S; Solgaard O; Miller DAB
    Science; 2023 Apr; 380(6643):398-404. PubMed ID: 37104594
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Memristors for Neuromorphic Circuits and Artificial Intelligence Applications.
    Miranda E; Suñé J
    Materials (Basel); 2020 Feb; 13(4):. PubMed ID: 32093164
    [TBL] [Abstract][Full Text] [Related]  

  • 6. DANTE: Deep alternations for training neural networks.
    Sinha VB; Kudugunta S; Sankar AR; Chavali ST; Balasubramanian VN
    Neural Netw; 2020 Nov; 131():127-143. PubMed ID: 32771843
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Noise can speed backpropagation learning and deep bidirectional pretraining.
    Kosko B; Audhkhasi K; Osoba O
    Neural Netw; 2020 Sep; 129():359-384. PubMed ID: 32599541
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Physical deep learning with biologically inspired training method: gradient-free approach for physical hardware.
    Nakajima M; Inoue K; Tanaka K; Kuniyoshi Y; Hashimoto T; Nakajima K
    Nat Commun; 2022 Dec; 13(1):7847. PubMed ID: 36572696
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey.
    Dampfhoffer M; Mesquida T; Valentian A; Anghel L
    IEEE Trans Neural Netw Learn Syst; 2024 Sep; 35(9):11906-11921. PubMed ID: 37027264
    [TBL] [Abstract][Full Text] [Related]  

  • 10. On the relationship between predictive coding and backpropagation.
    Rosenbaum R
    PLoS One; 2022; 17(3):e0266102. PubMed ID: 35358258
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks.
    Mostafa H; Pedroni B; Sheik S; Cauwenberghs G
    Front Neurosci; 2017; 11():496. PubMed ID: 28932180
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures.
    Lee C; Sarwar SS; Panda P; Srinivasan G; Roy K
    Front Neurosci; 2020; 14():119. PubMed ID: 32180697
    [TBL] [Abstract][Full Text] [Related]  

  • 13. SSTDP: Supervised Spike Timing Dependent Plasticity for Efficient Spiking Neural Network Training.
    Liu F; Zhao W; Chen Y; Wang Z; Yang T; Jiang L
    Front Neurosci; 2021; 15():756876. PubMed ID: 34803591
    [TBL] [Abstract][Full Text] [Related]  

  • 14. The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.
    Oladyshkin S; Praditia T; Kroeker I; Mohammadi F; Nowak W; Otte S
    Neural Netw; 2023 Sep; 166():85-104. PubMed ID: 37480771
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Spike-Train Level Direct Feedback Alignment: Sidestepping Backpropagation for On-Chip Training of Spiking Neural Nets.
    Lee J; Zhang R; Zhang W; Liu Y; Li P
    Front Neurosci; 2020; 14():143. PubMed ID: 32231513
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Biologically plausible deep learning - But how far can we go with shallow networks?
    Illing B; Gerstner W; Brea J
    Neural Netw; 2019 Oct; 118():90-101. PubMed ID: 31254771
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep quantum neural networks on a superconducting processor.
    Pan X; Lu Z; Wang W; Hua Z; Xu Y; Li W; Cai W; Li X; Wang H; Song YP; Zou CL; Deng DL; Sun L
    Nat Commun; 2023 Jul; 14(1):4006. PubMed ID: 37414812
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep Learning With Spiking Neurons: Opportunities and Challenges.
    Pfeiffer M; Pfeil T
    Front Neurosci; 2018; 12():774. PubMed ID: 30410432
    [TBL] [Abstract][Full Text] [Related]  

  • 19. On-Chip Training Spiking Neural Networks Using Approximated Backpropagation With Analog Synaptic Devices.
    Kwon D; Lim S; Bae JH; Lee ST; Kim H; Seo YT; Oh S; Kim J; Yeom K; Park BG; Lee JH
    Front Neurosci; 2020; 14():423. PubMed ID: 32733180
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Sign backpropagation: An on-chip learning algorithm for analog RRAM neuromorphic computing systems.
    Zhang Q; Wu H; Yao P; Zhang W; Gao B; Deng N; Qian H
    Neural Netw; 2018 Dec; 108():217-223. PubMed ID: 30216871
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.