| Spatio-temporal backpropagation for training high-performance spiking neural networks Y Wu, L Deng, G Li, J Zhu, L Shi Frontiers in neuroscience 12, 331, 2018 | 759 | 2018 |
| Towards artificial general intelligence with hybrid Tianjic chip architecture J Pei, L Deng, S Song, M Zhao, Y Zhang, S Wu, G Wang, Z Zou, Z Wu, ... Nature 572 (7767), 106, 2019 | 685 | 2019 |
| Model compression and hardware acceleration for neural networks: A comprehensive survey L Deng, G Li, S Han, L Shi, Y Xie Proceedings of the IEEE 108 (4), 485-532, 2020 | 620 | 2020 |
| Direct training for spiking neural networks: Faster, larger, better Y Wu, L Deng, G Li, J Zhu, Y Xie, L Shi Proceedings of the AAAI Conference on Artificial Intelligence 33, 1311-1318, 2019 | 498 | 2019 |
| Going deeper with directly-trained larger spiking neural networks H Zheng, Y Wu, L Deng, Y Hu, G Li Proceedings of the AAAI conference on artificial intelligence 35 (12), 11062 …, 2021 | 273 | 2021 |
| Hygcn: A gcn accelerator with hybrid architecture M Yan, L Deng, X Hu, L Liang, Y Feng, X Ye, Z Zhang, D Fan, Y Xie 2020 IEEE International Symposium on High Performance Computer Architecture …, 2020 | 257 | 2020 |
| Rethinking the performance comparison between SNNS and ANNS L Deng, Y Wu, X Hu, L Liang, Y Ding, G Li, G Zhao, P Li, Y Xie Neural networks 121, 294-307, 2020 | 205 | 2020 |
| GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework L Deng, P Jiao, J Pei, Z Wu, G Li Neural Networks 100, 49-58, 2018 | 165* | 2018 |
| -Norm Batch Normalization for Efficient Training of Deep Neural Networks S Wu, G Li, L Deng, L Liu, D Wu, Y Xie, L Shi IEEE transactions on neural networks and learning systems 30 (7), 2043-2051, 2018 | 147 | 2018 |
| Deepsniffer: A dnn model extraction framework based on learning architectural hints X Hu, L Liang, S Li, L Deng, P Zuo, Y Ji, X Xie, Y Ding, C Liu, T Sherwood, ... Proceedings of the Twenty-Fifth International Conference on Architectural …, 2020 | 142* | 2020 |
| Power-efficient neural network with artificial dendrites X Li, J Tang, Q Zhang, B Gao, JJ Yang, S Song, W Wu, W Zhang, P Yao, ... Nature Nanotechnology 15 (9), 776-782, 2020 | 136 | 2020 |
| {GNNAdvisor}: An adaptive and efficient runtime system for {GNN} acceleration on {GPUs} Y Wang, B Feng, G Li, S Li, L Deng, Y Xie, Y Ding 15th USENIX symposium on operating systems design and implementation (OSDI …, 2021 | 106 | 2021 |
| Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences W He, YJ Wu, L Deng, G Li, H Wang, Y Tian, W Ding, W Wang, Y Xie Neural Networks 132, 108-120, 2020 | 102 | 2020 |
| Training high-performance and large-scale deep neural networks with full 8-bit integers Y Yang, L Deng, S Wu, T Yan, Y Xie, G Li Neural Networks, 2020 | 95 | 2020 |
| Tianjic: A unified and scalable chip bridging spike-based and continuous neural computation L Deng, G Wang, G Li, S Li, L Liang, M Zhu, Y Wu, Z Yang, Z Zou, J Pei, ... IEEE Journal of Solid-State Circuits 55 (8), 2228-2246, 2020 | 94 | 2020 |
| Alleviating irregularity in graph analytics acceleration: A hardware/software co-design approach M Yan, X Hu, S Li, A Basak, H Li, X Ma, I Akgun, Y Feng, P Gu, L Deng, ... Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019 | 74 | 2019 |
| Minimum-cost control of complex networks G Li, W Hu, G Xiao, L Deng, P Tang, J Pei, L Shi New Journal of Physics 18 (1), 013012, 2015 | 74 | 2015 |
| Sampling methods for efficient training of graph convolutional networks: A survey X Liu, M Yan, L Deng, G Li, X Ye, D Fan IEEE/CAA Journal of Automatica Sinica 9 (2), 205-234, 2021 | 67 | 2021 |
| Hitnet: Hybrid ternary recurrent neural network P Wang, X Xie, L Deng, G Li, D Wang, Y Xie Advances in Neural Information Processing Systems 31, 2018 | 59 | 2018 |
| Development of a neuromorphic computing system L Shi, J Pei, N Deng, D Wang, L Deng, Y Wang, Y Zhang, F Chen, M Zhao, ... 2015 IEEE international electron devices meeting (IEDM), 4.3. 1-4.3. 4, 2015 | 57 | 2015 |
Guoqi LiProfessor, Institue of Automation，Chinese Academy of Sciences，Previously Tsinghua UniversityVerified email at ia.ac.cn
