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 *

115 related articles for article (PubMed ID: 36086236)

  • 1. Kernel Temporal Differences for EEG-based Reinforcement Learning Brain Machine Interfaces.
    Thapa BR; Tangarife DR; Bae J
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():3327-3333. PubMed ID: 36086236
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Kernel temporal differences for neural decoding.
    Bae J; Sanchez Giraldo LG; Pohlmeyer EA; Francis JT; Sanchez JC; Príncipe JC
    Comput Intell Neurosci; 2015; 2015():481375. PubMed ID: 25866504
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A new method of concurrently visualizing states, values, and actions in reinforcement based brain machine interfaces.
    Bae J; Sanchez Giraldo LG; Pohlmeyer EA; Sanchez JC; Principe JC
    Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():5402-5. PubMed ID: 24110957
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Clustering Based Kernel Reinforcement Learning for Neural Adaptation in Brain-Machine Interfaces.
    Zhang X; Principe JC; Wang Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():6125-6128. PubMed ID: 30441732
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A Weight Transfer Mechanism for Kernel Reinforcement Learning Decoding in Brain-Machine Interfaces.
    Zhang X; Wang Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():3547-3550. PubMed ID: 31946644
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Kernel Temporal Difference based Reinforcement Learning for Brain Machine Interfaces
    Shen X; Zhang X; Wang Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():6721-6724. PubMed ID: 34892650
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals.
    Tayeb Z; Fedjaev J; Ghaboosi N; Richter C; Everding L; Qu X; Wu Y; Cheng G; Conradt J
    Sensors (Basel); 2019 Jan; 19(1):. PubMed ID: 30626132
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Intermediate Sensory Feedback Assisted Multi-Step Neural Decoding for Reinforcement Learning Based Brain-Machine Interfaces.
    Shen X; Zhang X; Huang Y; Chen S; Yu Z; Wang Y
    IEEE Trans Neural Syst Rehabil Eng; 2022; 30():2834-2844. PubMed ID: 36219654
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganization.
    Pohlmeyer EA; Mahmoudi B; Geng S; Prins NW; Sanchez JC
    PLoS One; 2014; 9(1):e87253. PubMed ID: 24498055
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Clustering Neural Patterns in Kernel Reinforcement Learning Assists Fast Brain Control in Brain-Machine Interfaces.
    Zhang X; Libedinsky C; So R; Principe JC; Wang Y
    IEEE Trans Neural Syst Rehabil Eng; 2019 Sep; 27(9):1684-1694. PubMed ID: 31403433
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Reinforcement learning via kernel temporal difference.
    Bae J; Chhatbar P; Francis JT; Sanchez JC; Principe JC
    Annu Int Conf IEEE Eng Med Biol Soc; 2011; 2011():5662-5. PubMed ID: 22255624
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Task Learning Over Multi-Day Recording via Internally Rewarded Reinforcement Learning Based Brain Machine Interfaces.
    Shen X; Zhang X; Huang Y; Chen S; Wang Y
    IEEE Trans Neural Syst Rehabil Eng; 2020 Dec; 28(12):3089-3099. PubMed ID: 33232240
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Neural Decoders Using Reinforcement Learning in Brain Machine Interfaces: A Technical Review.
    Girdler B; Caldbeck W; Bae J
    Front Syst Neurosci; 2022; 16():836778. PubMed ID: 36090185
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Cluster Kernel Reinforcement Learning-based Kalman Filter for Three-Lever Discrimination Task in Brain-Machine Interface.
    Song Z; Zhang X; Wang Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():690-693. PubMed ID: 36086404
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep-Learning-Based Automatic Selection of Fewest Channels for Brain-Machine Interfaces.
    Kim HS; Ahn MH; Min BK
    IEEE Trans Cybern; 2022 Sep; 52(9):8668-8680. PubMed ID: 33635816
    [TBL] [Abstract][Full Text] [Related]  

  • 16. EEG classification across sessions and across subjects through transfer learning in motor imagery-based brain-machine interface system.
    Zheng M; Yang B; Xie Y
    Med Biol Eng Comput; 2020 Jul; 58(7):1515-1528. PubMed ID: 32394192
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep learning with convolutional neural networks for EEG decoding and visualization.
    Schirrmeister RT; Springenberg JT; Fiederer LDJ; Glasstetter M; Eggensperger K; Tangermann M; Hutter F; Burgard W; Ball T
    Hum Brain Mapp; 2017 Nov; 38(11):5391-5420. PubMed ID: 28782865
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Neural Control of a Tracking Task via Attention-Gated Reinforcement Learning for Brain-Machine Interfaces.
    Wang Y; Wang F; Xu K; Zhang Q; Zhang S; Zheng X
    IEEE Trans Neural Syst Rehabil Eng; 2015 May; 23(3):458-67. PubMed ID: 25073173
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Recognition of EEG Signal Motor Imagery Intention Based on Deep Multi-View Feature Learning.
    Xu J; Zheng H; Wang J; Li D; Fang X
    Sensors (Basel); 2020 Jun; 20(12):. PubMed ID: 32575798
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Motor Imagery EEG Classification Using Capsule Networks.
    Ha KW; Jeong JW
    Sensors (Basel); 2019 Jun; 19(13):. PubMed ID: 31252557
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.