| Precise-spike-driven synaptic plasticity: Learning hetero-association of spatiotemporal spike patterns Q Yu, H Tang, KC Tan, H Li Plos one 8 (11), e78318, 2013 | 128 | 2013 |
| Rapid feedforward computation by temporal encoding and learning with spiking neurons Q Yu, H Tang, KC Tan, H Li IEEE transactions on neural networks and learning systems 24 (10), 1539-1552, 2013 | 127 | 2013 |
| A brain-inspired spiking neural network model with temporal encoding and learning Q Yu, H Tang, KC Tan, H Yu Neurocomputing 138, 3-13, 2014 | 72 | 2014 |
| A spiking neural network system for robust sequence recognition Q Yu, R Yan, H Tang, KC Tan, H Li IEEE Transactions on Neural Networks and Learning Systems 27 (3), 621 - 635, 2016 | 65 | 2016 |
| Temporal coding of local spectrogram features for robust sound recognition J Dennis, Q Yu, H Tang, HD Tran, H Li 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 51 | 2013 |
| Spike timing or rate? Neurons learn to make decisions for both through threshold-driven plasticity Q Yu, H Li, KC Tan IEEE transactions on cybernetics 49 (6), 2178-2189, 2019 | 26 | 2019 |
| Neuromorphic Cognitive Systems Q Yu, H Tang, J Hu, KC Tan A Learning and Memory Centered Approach, 2017 | 15 | 2017 |
| Pattern recognition computation in a spiking neural network with temporal encoding and learning Q Yu, KC Tan, H Tang The 2012 International Joint Conference on Neural Networks (IJCNN), 1-7, 2012 | 15 | 2012 |
| Robust environmental sound recognition with sparse key-point encoding and efficient multi-spike learning Q Yu, Y Yao, L Wang, H Tang, J Dang, KC Tan IEEE Transactions on Neural Networks and Learning Systems, 2020 | 10 | 2020 |
| Gender-aware CNN-BLSTM for speech emotion recognition L Zhang, L Wang, J Dang, L Guo, Q Yu International Conference on Artificial Neural Networks, 782-790, 2018 | 9 | 2018 |
| Efficient multi-spike learning with tempotron-like ltp and psd-like ltd Q Yu, L Wang, J Dang International Conference on Neural Information Processing, 545-554, 2018 | 6 | 2018 |
| A bio-inspired feedforward system for categorization of AER motion events B Zhao, Q Yu, H Yu, S Chen, H Tang 2013 IEEE Biomedical Circuits and Systems Conference (BioCAS), 9-12, 2013 | 5 | 2013 |
| Learning real-world stimuli by single-spike coding and tempotron rule H Tang, Q Yu, KC Tan The 2012 International Joint Conference on Neural Networks (IJCNN), 1-6, 2012 | 5 | 2012 |
| Neuronal classifier for both rate and timing-based spike patterns Q Yu, L Wang, J Dang International Conference on Neural Information Processing, 759-766, 2017 | 4 | 2017 |
| Rapid feedforward computation by temporal encoding and learning with spiking neurons Q Yu, H Tang, J Hu, KC Tan Neuromorphic Cognitive Systems, 19-41, 2017 | 4 | 2017 |
| Associative memory model of hippocampus CA3 using spike response neurons CH Tan, EY Cheu, J Hu, Q Yu, H Tang International conference on neural information processing, 493-500, 2011 | 4 | 2011 |
| Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons. R Xiao, Q Yu, R Yan, H Tang IJCAI, 1445-1451, 2019 | 3 | 2019 |
| A multi-spike approach for robust sound recognition Q Yu, Y Yao, L Wang, H Tang, J Dang ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 3 | 2019 |
| A hierarchically organized memory model with temporal population coding Q Yu, H Tang, J Hu, KC Tan Neuromorphic Cognitive Systems, 131-152, 2017 | 3 | 2017 |
| Temporal learning in multilayer spiking neural networks through construction of causal connections Q Yu, H Tang, J Hu, KC Tan Neuromorphic Cognitive Systems, 115-129, 2017 | 2 | 2017 |
