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2020 – today
- 2024
[j40]Yu Tang
, Shangqi Guo, Jinhui Liu, Bo Wan, Lingling An, Jian K. Liu:
Hierarchical reinforcement learning from imperfect demonstrations through reachable coverage-based subgoal filtering. Knowl. Based Syst. 294: 111736 (2024)- [j39]Yunhua Chen, Ren Feng, Zhimin Xiong, Jinsheng Xiao, Jian K. Liu:
High-performance deep spiking neural networks via at-most-two-spike exponential coding. Neural Networks 176: 106346 (2024) - [j38]Ye Chen, Peter Beech, Ziwei Yin, Shanshan Jia, Jiayi Zhang, Zhaofei Yu, Jian K. Liu:
Decoding dynamic visual scenes across the brain hierarchy. PLoS Comput. Biol. 20(8): 1012297 (2024) - [j37]Yaxin Li, Xuanye Fang, Yuyuan Gao, Dongdong Zhou, Jiangrong Shen, Jian K. Liu, Gang Pan, Qi Xu:
Efficient Structure Slimming for Spiking Neural Networks. IEEE Trans. Artif. Intell. 5(8): 3823-3831 (2024) - [j36]Qi Xu, Yaxin Li, Jiangrong Shen, Pingping Zhang, Jian K. Liu, Huajin Tang, Gang Pan:
Hierarchical Spiking-Based Model for Efficient Image Classification With Enhanced Feature Extraction and Encoding. IEEE Trans. Neural Networks Learn. Syst. 35(7): 9277-9285 (2024) - [j35]Gen Shi, Yifan Zhu, Jian K. Liu, Xuesong Li:
HeGCL: Advance Self-Supervised Learning in Heterogeneous Graph-Level Representation. IEEE Trans. Neural Networks Learn. Syst. 35(10): 13914-13925 (2024) - [c9]Jianhao Ding, Zhaofei Yu, Tiejun Huang, Jian K. Liu:
Enhancing the Robustness of Spiking Neural Networks with Stochastic Gating Mechanisms. AAAI 2024: 492-502 - [c8]Rining Wu, Feixiang Zhou, Ziwei Yin, Jian K. Liu:
Aligning Neuronal Coding of Dynamic Visual Scenes with Foundation Vision Models. ECCV (88) 2024: 238-254 - [i15]Peter Beech, Shanshan Jia, Zhaofei Yu, Jian K. Liu:
Deep Learning for Visual Neuroprosthesis. CoRR abs/2401.03639 (2024) - [i14]Zhipeng Huang, Jianhao Ding, Zhiyu Pan, Haoran Li, Ying Fang, Zhaofei Yu, Jian K. Liu:
Converting High-Performance and Low-Latency SNNs through Explicit Modelling of Residual Error in ANNs. CoRR abs/2404.17456 (2024) - [i13]Rining Wu, Feixiang Zhou, Ziwei Yin, Jian K. Liu:
Aligning Neuronal Coding of Dynamic Visual Scenes with Foundation Vision Models. CoRR abs/2407.10737 (2024) - 2023
- [j34]Long Chen, Rining Wu, Feixiang Zhou, Huifeng Zhang, Jian K. Liu:
HybridGCN for protein solubility prediction with adaptive weighting of multiple features. J. Cheminformatics 15(1): 118 (2023) - [j33]Wenju Yang, Jiankang Liu, Peng Cao, Rongxin Zhu, Yang Wang, Jian K. Liu, Fei Wang, Xizhe Zhang:
Attention guided learnable time-domain filterbanks for speech depression detection. Neural Networks 165: 135-149 (2023) - [j32]Yuanhong Tang, Xingyu Zhang, Lingling An, Zhaofei Yu, Jian K. Liu:
Diverse role of NMDA receptors for dendritic integration of neural dynamics. PLoS Comput. Biol. 19(4) (2023) - [j31]Qiongyi Zhou, Changde Du, Dan Li, Haibao Wang, Jian K. Liu, Huiguang He:
Neural Encoding and Decoding With a Flow-Based Invertible Generative Model. IEEE Trans. Cogn. Dev. Syst. 15(2): 724-736 (2023) - [j30]Lingling An, Ye Yuan, Yunhao Liu, Fan Zhao, Quan Wang, Jian K. Liu:
Flexible Learning Models Utilizing Different Neural Plasticities. IEEE Trans. Cogn. Dev. Syst. 15(3): 1150-1160 (2023) - [j29]Lingling An, Zhen Yan, Weizheng Wang, Jian K. Liu, Keping Yu:
Enhancing Visual Coding Through Collaborative Perception. IEEE Trans. Cogn. Dev. Syst. 15(4): 1744-1753 (2023) - [j28]Mingxu Li, Bo Peng, Jian K. Liu, Donghai Zhai:
RBNet: An Ultrafast Rendering-Based Architecture for Railway Defect Segmentation. IEEE Trans. Instrum. Meas. 72: 1-8 (2023) - [j27]Jiangrong Shen, Yu Zhao, Jian K. Liu, Yueming Wang:
HybridSNN: Combining Bio-Machine Strengths by Boosting Adaptive Spiking Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5841-5855 (2023) - [c7]Jiangrong Shen, Qi Xu, Jian K. Liu, Yueming Wang, Gang Pan, Huajin Tang:
ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks. AAAI 2023: 86-93 - [c6]Qi Xu, Yaxin Li, Jiangrong Shen, Jian K. Liu, Huajin Tang, Gang Pan:
Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation. CVPR 2023: 7886-7895 - [i12]Qi Xu, Yaxin Li, Jiangrong Shen, Jian K. Liu, Huajin Tang, Gang Pan:
Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation. CoRR abs/2304.05627 (2023) - [i11]Qi Xu, Yaxin Li, Xuanye Fang, Jiangrong Shen, Jian K. Liu, Huajin Tang, Gang Pan:
Biologically inspired structure learning with reverse knowledge distillation for spiking neural networks. CoRR abs/2304.09500 (2023) - [i10]Jiangrong Shen, Qi Xu, Jian K. Liu, Yueming Wang, Gang Pan, Huajin Tang:
ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks. CoRR abs/2306.03693 (2023) - [i9]Jianhao Ding, Zhaofei Yu, Tiejun Huang, Jian K. Liu:
Spike timing reshapes robustness against attacks in spiking neural networks. CoRR abs/2306.05654 (2023) - 2022
- [j26]Chuanliang Han, Tian Wang, Yujie Wu, Hui Li, Encong Wang, Xixi Zhao, Qingjiu Cao, Qiujin Qian, Yufeng Wang, Fei Dou, Jian K. Liu, Li Sun, Dajun Xing:
Compensatory mechanism of attention-deficit/hyperactivity disorder recovery in resting state alpha rhythms. Frontiers Comput. Neurosci. 16 (2022) - [j25]Yi-Jun Zhang, Zhaofei Yu, Jian K. Liu, Tie-Jun Huang:
Neural Decoding of Visual Information Across Different Neural Recording Modalities and Approaches. Int. J. Autom. Comput. 19(5): 350-365 (2022) - [j24]Yijun Zhang, Tong Bu, Jiyuan Zhang, Shiming Tang, Zhaofei Yu, Jian K. Liu, Tiejun Huang:
Decoding Pixel-Level Image Features From Two-Photon Calcium Signals of Macaque Visual Cortex. Neural Comput. 34(6): 1369-1397 (2022) - [j23]Shanshan Jia, Xingyi Li, Tiejun Huang, Jian K. Liu, Zhaofei Yu:
Representing the dynamics of high-dimensional data with non-redundant wavelets. Patterns 3(3): 100424 (2022) - [j22]Jian K. Liu, Dimokratis Karamanlis, Tim Gollisch:
Simple model for encoding natural images by retinal ganglion cells with nonlinear spatial integration. PLoS Comput. Biol. 18(3) (2022) - [j21]Qi Yan, Yajing Zheng, Shanshan Jia, Yichen Zhang, Zhaofei Yu, Feng Chen, Yonghong Tian, Tiejun Huang, Jian K. Liu:
Revealing Fine Structures of the Retinal Receptive Field by Deep-Learning Networks. IEEE Trans. Cybern. 52(1): 39-50 (2022) - [j20]Shanshan Jia, Zhaofei Yu, Arno Onken, Yonghong Tian, Tie-Jun Huang, Jian K. Liu:
Neural System Identification With Spike-Triggered Non-Negative Matrix Factorization. IEEE Trans. Cybern. 52(6): 4772-4783 (2022) - [j19]Qi Xu, Jiangrong Shen, Xuming Ran, Huajin Tang, Gang Pan, Jian K. Liu:
Robust Transcoding Sensory Information With Neural Spikes. IEEE Trans. Neural Networks Learn. Syst. 33(5): 1935-1946 (2022) - [c5]Zhile Yang, Shangqi Guo, Ying Fang, Jian K. Liu:
Biologically Plausible Variational Policy Gradient with Spiking Recurrent Winner-Take-All Networks. BMVC 2022: 358 - [c4]Jianhao Ding, Tong Bu, Zhaofei Yu, Tiejun Huang, Jian K. Liu:
SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training. NeurIPS 2022 - [i8]Zhile Yang, Shangqi Guo, Ying Fang, Jian K. Liu:
Biologically Plausible Variational Policy Gradient with Spiking Recurrent Winner-Take-All Networks. CoRR abs/2210.13225 (2022) - 2021
- [j18]Jiangrong Shen, Jian K. Liu, Yueming Wang:
Dynamic Spatiotemporal Pattern Recognition With Recurrent Spiking Neural Network. Neural Comput. 33(11): 2971-2995 (2021) - [j17]Yajing Zheng, Shanshan Jia, Zhaofei Yu, Jian K. Liu, Tiejun Huang:
Unraveling neural coding of dynamic natural visual scenes via convolutional recurrent neural networks. Patterns 2(10): 100350 (2021) - [j16]Yuanhong Tang, Lingling An, Ye Yuan, Qingqi Pei, Quan Wang, Jian K. Liu:
Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways. PLoS Comput. Biol. 17(2) (2021) - [j15]Yuanhong Tang, Lingling An, Quan Wang, Jian K. Liu:
Regulating synchronous oscillations of cerebellar granule cells by different types of inhibition. PLoS Comput. Biol. 17(6) (2021) - [j14]Shanshan Jia, Dajun Xing, Zhaofei Yu, Jian K. Liu:
Dissecting cascade computational components in spiking neural networks. PLoS Comput. Biol. 17(11) (2021) - 2020
- [j13]Lingling An, Yuanhong Tang, Doudou Wang, Shanshan Jia, Qingqi Pei, Quan Wang, Zhaofei Yu, Jian K. Liu:
Intrinsic and Synaptic Properties Shaping Diverse Behaviors of Neural Dynamics. Frontiers Comput. Neurosci. 14: 26 (2020) - [j12]Yichen Zhang, Shanshan Jia, Yajing Zheng, Zhaofei Yu, Yonghong Tian, Siwei Ma, Tiejun Huang, Jian K. Liu:
Reconstruction of natural visual scenes from neural spikes with deep neural networks. Neural Networks 125: 19-30 (2020) - [j11]Yajing Zheng, Shanshan Jia, Zhaofei Yu, Tiejun Huang, Jian K. Liu, Yonghong Tian:
Probabilistic inference of binary Markov random fields in spiking neural networks through mean-field approximation. Neural Networks 126: 42-51 (2020) - [j10]Zhaofei Yu, Feng Chen, Jian K. Liu:
Sampling-Tree Model: Efficient Implementation of Distributed Bayesian Inference in Neural Networks. IEEE Trans. Cogn. Dev. Syst. 12(3): 497-510 (2020) - [j9]Zhaofei Yu, Shangqi Guo, Fei Deng, Qi Yan, Keke Huang, Jian K. Liu, Feng Chen:
Emergent Inference of Hidden Markov Models in Spiking Neural Networks Through Winner-Take-All. IEEE Trans. Cybern. 50(3): 1347-1354 (2020) - [c3]Jiangrong Shen, Yu Zhao, Jian K. Liu, Yueming Wang:
Recognizing Scoring in Basketball Game from AER Sequence by Spiking Neural Networks. IJCNN 2020: 1-8 - [c2]Qiongyi Zhou, Changde Du, Dan Li, Haibao Wang, Jian K. Liu, Huiguang He:
Simultaneous Neural Spike Encoding and Decoding Based on Cross-modal Dual Deep Generative Model. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [j8]Xueqing Zhao, Xin Shi, Bo Yang, Quanli Gao, Zhaofei Yu, Jian K. Liu, Yonghong Tian, Tiejun Huang:
Skeleton-Based 3D Object Retrieval Using Retina-Like Feature Descriptor. IEEE Access 7: 157341-157352 (2019) - [j7]Lingling An, Yuanhong Tang, Quan Wang, Qingqi Pei, Ran Wei, Huiyuan Duan, Jian K. Liu:
Coding Capacity of Purkinje Cells With Different Schemes of Morphological Reduction. Frontiers Comput. Neurosci. 13: 29 (2019) - [j6]Gautham P. Das, Philip J. Vance, Dermot Kerr, Sonya A. Coleman, T. Martin McGinnity, Jian K. Liu:
Computational modelling of salamander retinal ganglion cells using machine learning approaches. Neurocomputing 325: 101-112 (2019) - [j5]Ying Fang, Zhaofei Yu, Jian K. Liu, Feng Chen:
A unified neural circuit of causal inference and multisensory integration. Neurocomputing 358: 355-368 (2019) - [i7]Yajing Zheng, Zhaofei Yu, Shanshan Jia, Jian K. Liu, Tiejun Huang, Yonghong Tian:
Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field Approximation. CoRR abs/1902.08411 (2019) - [i6]Yichen Zhang, Shanshan Jia, Yajing Zheng, Zhaofei Yu, Yonghong Tian, Tiejun Huang, Jian K. Liu:
Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks. CoRR abs/1904.13007 (2019) - 2018
- [j4]Philip J. Vance, Gautham P. Das, Dermot Kerr, Sonya A. Coleman, T. Martin McGinnity, Tim Gollisch, Jian K. Liu:
Bioinspired Approach to Modeling Retinal Ganglion Cells Using System Identification Techniques. IEEE Trans. Neural Networks Learn. Syst. 29(5): 1796-1808 (2018) - [c1]Zhaofei Yu, Tiejun Huang, Jian K. Liu:
Implementation of Bayesian Inference In Distributed Neural Networks. PDP 2018: 666-673 - [i5]Yang Yue, Liuyuan He, Gan He, Jian K. Liu, Kai Du, Yonghong Tian, Tiejun Huang:
A simple blind-denoising filter inspired by electrically coupled photoreceptors in the retina. CoRR abs/1806.05882 (2018) - [i4]Zhaofei Yu, Yonghong Tian, Tiejun Huang, Jian K. Liu:
Winner-Take-All as Basic Probabilistic Inference Unit of Neuronal Circuits. CoRR abs/1808.00675 (2018) - [i3]Shanshan Jia, Zhaofei Yu, Arno Onken, Yonghong Tian, Tiejun Huang, Jian K. Liu:
Characterizing Neuronal Circuits with Spike-triggered Non-negative Matrix Factorization. CoRR abs/1808.03958 (2018) - [i2]Qi Yan, Yajing Zheng, Shanshan Jia, Yichen Zhang, Zhaofei Yu, Feng Chen, Yonghong Tian, Tiejun Huang, Jian K. Liu:
Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks. CoRR abs/1811.02290 (2018) - 2017
- [i1]Qi Yan, Zhaofei Yu, Feng Chen, Jian K. Liu:
Revealing structure components of the retina by deep learning networks. CoRR abs/1711.02837 (2017) - 2016
- [j3]Arno Onken, Jian K. Liu, P. P. Chamanthi R. Karunasekara, Ioannis Delis, Tim Gollisch, Stefano Panzeri:
Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains. PLoS Comput. Biol. 12(11) (2016) - 2015
- [j2]Jian K. Liu, Tim Gollisch:
Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina. PLoS Comput. Biol. 11(7) (2015) - 2011
- [j1]Jian K. Liu:
Learning Rule of Homeostatic Synaptic Scaling: Presynaptic Dependent or Not. Neural Comput. 23(12): 3145-3161 (2011)
Coauthor Index
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