Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner JK Liu, DV Buonomano Journal of Neuroscience 29 (42), 13172-13181, 2009 | 123 | 2009 |
Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization JK Liu, HM Schreyer, A Onken, F Rozenblit, MH Khani, V Krishnamoorthy, ... Nature communications 8 (1), 149, 2017 | 111 | 2017 |
Using matrix and tensor factorizations for the single-trial analysis of population spike trains A Onken, JK Liu, PPCR Karunasekara, I Delis, T Gollisch, S Panzeri PLoS computational biology 12 (11), e1005189, 2016 | 79 | 2016 |
Constructing deep spiking neural networks from artificial neural networks with knowledge distillation Q Xu, Y Li, J Shen, JK Liu, H Tang, G Pan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 68 | 2023 |
Spike-triggered covariance analysis reveals phenomenological diversity of contrast adaptation in the retina JK Liu, T Gollisch PLoS computational biology 11 (7), e1004425, 2015 | 58 | 2015 |
Reconstruction of natural visual scenes from neural spikes with deep neural networks Y Zhang, S Jia, Y Zheng, Z Yu, Y Tian, S Ma, T Huang, JK Liu Neural Networks 125, 19-30, 2020 | 55 | 2020 |
Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar circuit V Zampini*, JK Liu*, MA Diana, PP Maldonado, N Brunel, S Dieudonné eLife 5, e15872, 2016 | 52 | 2016 |
Single-neuron representation of learned complex sounds in the auditory cortex M Wang, X Liao, R Li, S Liang, R Ding, J Li, J Zhang, W He, K Liu, J Pan, ... Nature communications 11 (1), 4361, 2020 | 51 | 2020 |
Toward the next generation of retinal neuroprosthesis: visual computation with spikes Z Yu, JK Liu, S Jia, Y Zhang, Y Zheng, Y Tian, T Huang Engineering 6 (4), 449-461, 2020 | 49 | 2020 |
Hierarchical Spiking-Based Model for Efficient Image Classification With Enhanced Feature Extraction and Encoding Q Xu, Y Li, J Shen, P Zhang, JK Liu, H Tang, G Pan IEEE Transactions on Neural Networks and Learning Systems 35 (7), 9277-9285, 2024 | 43 | 2024 |
Esl-snns: An evolutionary structure learning strategy for spiking neural networks J Shen, Q Xu, JK Liu, Y Wang, G Pan, H Tang Proceedings of the AAAI Conference on Artificial Intelligence 37 (1), 86-93, 2023 | 40 | 2023 |
Robust transcoding sensory information with neural spikes Q Xu, J Shen, X Ran, H Tang, G Pan, JK Liu IEEE Transactions on Neural Networks and Learning Systems 33 (5), 1935-1946, 2022 | 39 | 2022 |
Revealing fine structures of the retinal receptive field by deep-learning networks Q Yan, Y Zheng, S Jia, Y Zhang, Z Yu, F Chen, Y Tian, T Huang, JK Liu IEEE transactions on cybernetics 5, 2022 | 35 | 2022 |
MATRIEX imaging: multiarea two-photon real-time in vivo explorer M Yang, Z Zhou, J Zhang, S Jia, T Li, J Guan, X Liao, B Leng, J Lyu, ... Light: Science & Applications 8 (1), 109, 2019 | 35 | 2019 |
Unraveling neural coding of dynamic natural visual scenes via convolutional recurrent neural networks Y Zheng, S Jia, Z Yu, JK Liu, T Huang Patterns 2 (10), 100350, 2021 | 34 | 2021 |
SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training J Ding, T Bu, Z Yu, T Huang, JK Liu Advances in Neural Information Processing Systems, 2022 | 31 | 2022 |
Emergent inference of hidden markov models in spiking neural networks through winner-take-all Z Yu, S Guo, F Deng, Q Yan, K Huang, JK Liu, F Chen IEEE transactions on cybernetics 50 (3), 1347-1354, 2018 | 26 | 2018 |
HybridSNN: Combining Bio-Machine Strengths by Boosting Adaptive Spiking Neural Networks J Shen, Y Zhao, JK Liu, Y Wang IEEE Transactions on Neural Networks and Learning Systems 34, 5841-5855, 2023 | 25 | 2023 |
Simple model for encoding natural images by retinal ganglion cells with nonlinear spatial integration JK Liu, D Karamanlis, T Gollisch PLOS Computational Biology 18 (3), e1009925, 2022 | 24 | 2022 |
Learning rule of homeostatic synaptic scaling: Presynaptic dependent or not JK Liu Neural computation 23 (12), 3145-3161, 2011 | 23 | 2011 |