| Improving support vector machine classifiers by modifying kernel functions S Amari, S Wu Neural networks 12 (6), 783-789, 1999 | 1365 | 1999 |
| 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), 106-111, 2019 | 1054 | 2019 |
| Spiking neurons with spatiotemporal dynamics and gain modulation for monolithically integrated memristive neural networks Q Duan, Z Jing, X Zou, Y Wang, K Yang, T Zhang, S Wu, R Huang, ... Nature communications 11 (1), 3399, 2020 | 281 | 2020 |
| A dynamic call admission policy with precision QoS guarantee using stochastic control for mobile wireless networks S Wu, KYM Wong, B Li IEEE/ACM Transactions on Networking 10 (2), 257-271, 2002 | 191 | 2002 |
| Population coding and decoding in a neural field: a computational study S Wu, S Amari, H Nakahara Neural Computation 14 (5), 999-1026, 2002 | 185 | 2002 |
| Sequential support vector classifiers and regression S Vijayakumar, S Wu Proc. International Conference on Soft Computing (SOCO'99), Genoa, Italy, 1999 | 163 | 1999 |
| Synchronous firing and higher-order interactions in neuron pool S Amari, H Nakahara, S Wu, Y Sakai Neural computation 15 (1), 127-142, 2003 | 155 | 2003 |
| Perceptual training continuously refines neuronal population codes in primary visual cortex Y Yan, MJ Rasch, M Chen, X Xiang, M Huang, S Wu, W Li Nature neuroscience 17 (10), 1380-1387, 2014 | 148 | 2014 |
| Conformal transformation of kernel functions: A data-dependent way to improve support vector machine classifiers S Wu, SI Amari Neural Processing Letters 15, 59-67, 2002 | 142 | 2002 |
| Action potential initiation in neocortical inhibitory interneurons T Li, C Tian, P Scalmani, C Frassoni, M Mantegazza, Y Wang, M Yang, ... PLoS biology 12 (9), e1001944, 2014 | 129 | 2014 |
| Dynamics and computation of continuous attractors S Wu, K Hamaguchi, S Amari Neural computation 20 (4), 994-1025, 2008 | 125 | 2008 |
| A moving bump in a continuous manifold: a comprehensive study of the tracking dynamics of continuous attractor neural networks CCA Fung, KYM Wong, S Wu Neural Computation 22 (3), 752-792, 2010 | 105 | 2010 |
| Population coding with correlation and an unfaithful model S Wu, H Nakahara, S Amari Neural computation 13 (4), 775-797, 2001 | 102 | 2001 |
| Compensating time delays with neural predictions: are predictions sensory or motor? R Nijhawan, S Wu Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2009 | 91 | 2009 |
| Dynamic lipidome alterations associated with human health, disease and ageing D Hornburg, S Wu, M Moqri, X Zhou, K Contrepois, N Bararpour, ... Nature metabolism 5 (9), 1578-1594, 2023 | 88 | 2023 |
| 1000× faster camera and machine vision with ordinary devices T Huang, Y Zheng, Z Yu, R Chen, Y Li, R Xiong, L Ma, J Zhao, S Dong, ... Engineering 25, 110-119, 2023 | 82 | 2023 |
| Computing with continuous attractors: stability and online aspects S Wu, S Amari Neural computation 17 (10), 2215-2239, 2005 | 82 | 2005 |
| Short-term synaptic plasticity M Tsodyks, S Wu Scholarpedia 8 (10), 3153, 2013 | 81 | 2013 |
| Genomic basis underlying the metabolome-mediated drought adaptation of maize F Zhang, J Wu, N Sade, S Wu, A Egbaria, AR Fernie, J Yan, F Qin, ... Genome Biology 22, 1-26, 2021 | 79 | 2021 |
| Continuous attractor neural networks: candidate of a canonical model for neural information representation S Wu, KYM Wong, CCA Fung, Y Mi, W Zhang F1000Research 5, F1000 Faculty Rev-156, 2016 | 75 | 2016 |