中心论文选登

期刊论文 Journal Papers

2020

[1]      施路平,裴京,赵蓉. “面向人工通用智能的类脑计算”. 人工智能 : 类脑计算与脑科学. 2020(1):6-15. (《人工智能》杂志由工业和信息化部主管,中国电子信息产业发展研究院、赛迪工业和信息化研究院(集团)有限公司主办(CN10-1530/TP,ISSN2096-5036))

[2]     Z. Chen, L. Deng, B. Wang,G. Li* and Y. Xie, A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks, IEEE Transactions on Pattern Machine Intelligence (IEEE TPAMI), Accepted, in press, 2020.

[3]      L. Deng, G. Li*, H. Song, Y. Xie and L. Shi, Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey, Proceedings of the IEEE (PIEEE), 108 (4), 485-532, 2020.

[4]      L. Tian, Z. Z. Wu, S. Wu, L.P. Shi*, “Hybrid Neural State Machine for neural network”, Journal of SCIENCE CHINA Information Sciences(2020)

[5]      Z. Chen, L. Deng, G. Li*, J. Sun, X. Hu, L. Liang and Y. Xie, Effective and Efficient Batch Normalization Using Few Uncorrelated Data for Statistics’ Estimation, IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), Accepted, in press, 2020.

[6]      L.Deng, G. Wang, G. Li , S. Li, L Liang, M Zhu, Y Wu, Z Yang, Z Zou, Z.Wu, X.Hu, Y.Ding, W. He, Y. Xie, L. Shi* , Tianjic: A Unified and Scalable Chip Bridging Spike-Based and Continuous Neural Computation, IEEE Journal of Solid-State Circuits (IEEE JSSC), vol. 55, pp. 2228 – 2246, 2020.

[7]      L. Deng, L. Liang , G. Wang, L. Chang, X. Hu, L. Liu, J. Pei, G. Li* and Y.Xie, SemiMap: A Semi-folded Convolution Mapping for Speed-Overhead Balance on Crossbars,IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD), vol. 39, pp.117-130, 2020.

[8]     D. Wang, G. Zhao,G. Li*, L. Deng, Y. Wu, Compressing 3DCNNs based on Tensor Train Decomposition, Neural Networks, Accepted, in press, 2020.

[9]     L. Deng, Y. Wu, X. Hu, L. Liang, Y. Ding, G. Li, G*. Zhao, P. Li, Y. Xie, Rethinking the performance comparison between SNNS and ANNS, Neural Networks, 121, 294-307, 2020.

[10]    B. Wu, D. Wang, G. Zhao, L. Deng and G. Li*, Hybrid Tensor Decomposition in Neural Network Compression, Neural Networks, Accepted, in press, 2020.

[11]    Lyu, J. , Pei, J. , Guo, Y. , Gong, J. , & Li, H*.. A New Opportunity for 2D van der Waals Heterostructures: Making Steep‐Slope Transistors. Advanced Materials, 2020, 32(2).

2019

[1]      J. Pei, L. Deng, S. Song, M. Zhao, Y. Zhang, S. Wu, G. Wang, Z. Zou, Z. Wu, W. He, F. Chen, N. Deng, S. Wu, Y. Wang, Y. Wu, Z. Yang, C. Ma, G. Li, W. Han, H. Li, H. Wu, R. Zhao, Y. Xie & L.P. Shi*, “Towards artificial general intelligence with hybrid Tianjic chip architecture”, Nature, 572, pp106-111, (2019).

[2]      Y. Yang, L. Deng, S. Wu, T. Yan, Y. Xie and G. Li*, Training high-performance and large-scale deep neural networks with full 8-bit integers, Neural Networks, 121, 294-307, 2019.   

[3]      K. Song, X. Chen, P. Tang,G. Li*, L. Deng and J. Pei, Target Controllability of Two-layer Multiplex Networks based on Network Flow Theory, IEEE Transactions on Cybernetics, Accepted, in press, 2019.

[4]      Z.Y. Zhang, T.R. Li, Y.J. Wu, Y.J. Jia, C.W. Tan, X.T. Xu, G.R. Wang, J. Lv, W. Zhang, Y.H. He, J. Pei, C. Ma, G.Q. Li, H.Z. Xu, L.P. Shi*, H.L. Peng, H.L. Li, “Truly Concomitant and Independently Expressed Short‐and Long‐Term Plasticity in a Bi2O2Se‐Based Three‐Terminal Memristor”, Advanced Materials, 31(3) 1805769, (2019)

[5]      S. Wu, G.Q. Li, L. Deng, L. Liu, Y. Xie, L.P. Shi*, “L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks”, IEEE Transactions on Neural Networks and Learning Systems, 30(7), pp2043-2051, (2019)

[6]      Y.Y. Wang, Z.Y. Zhang, M.K. Xu, Y.F. Yang, M.Y. Ma, H.L. Li, J. Pei, L.P. Shi*, “Self-doping memristors with equivalently synaptic ion dynamics for neuromorphic computing”, ACS Applied Materials & Interfaces, 11(27) pp24230-24240, (2019) 

2018

[1]      L. Deng, P. Jiao, J. Pei, Z. W and G. Li*, GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework, Neural Networks, vol.100, pp.49-58, 2018.

[2]      Y. Zhang & W. He, Y. Wu, K. Huang, Y. Shen, J. Su, Y. Wang, Z.Y. Zhang, X.L. Ji, G.Q. Li, H.T. Zhang, S. Song, H.L. Li, L.T. Sun, R. Zhao, L.P. Shi*, “Highly Compact Artificial Memristive Neuron with Low Energy Consumption”, Small, 14(51) pp1802188, (2018)

[3]      G.Q. Li, L. Deng, L. Tian, H. Cui, W. Han, J. Pei, L.P. Shi*, “Training deep neural networks with discrete state transition”, Neurocomputing, 272, 154-162, (2018)

[4]      Y. Wu, L. Deng, G. Li J. Zhu, L. Shi*, Spatio-temporal Backpropagation for Training High-performance Spiking Neural Networks,Frontiers in Neuroscience, 12, 331, 2018.

会议论文 Conference Papers

[1]      Y. Wu, L. Deng, G. Li, J. Zhu and L.Shi*, Direct Training Spiking Neural Networks: Faster, Larger and Better, Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019).

[2]      L. Liu, L. Deng, X. Hu, M. Zhu, G. Li, Y. Ding and Y Xie*, Dynamic Sparse Graph for Efficient Deep Learning,International Conference on Learning Representations (ICLR 2019).

[3]      S. Wu, G.R. Wang, P. Tang, F. Chen, L.P. Shi*, “Convolution with even-sized kernels and symmetric padding”, Conference on Neural Information Processing Systems (NeurIPS) (2019)

[4]      P. Wang, X.Xie, L. Deng, G. Li, D. Wang and Y. Xie*, HiNet: Hybrid Ternary Recurrent Neural Networks, Thirty-second Annual Conference on  Neural Information Processing Systems (NeurIPS 2018).

[5]      S. Wu, G. Li C. Feng and L.Shi*, Training and Inference with Integers in Deep Neural Networks, International Conference on Learning Representations  (ICLR 2018).


• 2020年9月20日编辑

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