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Shuncheng Jia

Showing results (1-10 of 6) with videos related to

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Frontiers in Neuroscience|April 6, 2023
Explaining cocktail party effect and McGurk effect with a spiking neural network improved by Motif-topologyShuncheng Jia, Tielin Zhang, Ruichen Zuo, et al.
IEEE Transactions on Neural Networks and Learning Systems|June 14, 2021
Tuning Convolutional Spiking Neural Network With Biologically Plausible Reward PropagationTielin Zhang, Shuncheng Jia, Xiang Cheng, et al.
Frontiers in Neuroscience|March 29, 2021
Neuronal-Plasticity and Reward-Propagation Improved Recurrent Spiking Neural NetworksShuncheng Jia, Tielin Zhang, Xiang Cheng, et al.
Science Advances|October 20, 2021
Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networksTielin Zhang, Xiang Cheng, Shuncheng Jia, et al.
Science Advances|August 25, 2023
A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational costTielin Zhang, Xiang Cheng, Shuncheng Jia, et al.
Communications Biology|January 28, 2025
Recurrent neural networks with transient trajectory explain working memory encoding mechanismsChenghao Liu, Shuncheng Jia, Hongxing Liu, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Frontiers in Neuroscience|April 6, 2023
Explaining cocktail party effect and McGurk effect with a spiking neural network improved by Motif-topologyShuncheng Jia, Tielin Zhang, Ruichen Zuo, et al.
IEEE Transactions on Neural Networks and Learning Systems|June 14, 2021
Tuning Convolutional Spiking Neural Network With Biologically Plausible Reward PropagationTielin Zhang, Shuncheng Jia, Xiang Cheng, et al.
Frontiers in Neuroscience|March 29, 2021
Neuronal-Plasticity and Reward-Propagation Improved Recurrent Spiking Neural NetworksShuncheng Jia, Tielin Zhang, Xiang Cheng, et al.
Science Advances|October 20, 2021
Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networksTielin Zhang, Xiang Cheng, Shuncheng Jia, et al.
Science Advances|August 25, 2023
A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational costTielin Zhang, Xiang Cheng, Shuncheng Jia, et al.
Communications Biology|January 28, 2025
Recurrent neural networks with transient trajectory explain working memory encoding mechanismsChenghao Liu, Shuncheng Jia, Hongxing Liu, et al.
Pageof 1