An attention-driven two-stage clustering method for unsupervised person re-identification Z Ji, X Zou, X Lin, X Liu, T Huang, S Wu Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 61 | 2020 |
A brain-inspired computational model for spatio-temporal information processing X Lin, X Zou, Z Ji, T Huang, S Wu, Y Mi Neural Networks 143, 74-87, 2021 | 14 | 2021 |
Neural computations in a dynamical system with multiple time scales Y Mi, X Lin, S Wu Frontiers in Computational Neuroscience 10, 96, 2016 | 11 | 2016 |
A just-in-time compilation approach for neural dynamics simulation C Wang, Y Jiang, X Liu, X Lin, X Zou, Z Ji, S Wu Neural Information Processing: 28th International Conference, ICONIP 2021 …, 2021 | 4 | 2021 |
Spatiotemporal information processing with a reservoir decision-making network Y Mi, X Lin, X Zou, Z Ji, T Huang, S Wu arXiv preprint arXiv:1907.12071, 2019 | 4 | 2019 |
Dynamical information encoding in neural adaptation L Li, W Zhang, Y Mi, D Wang, X Lin, S Wu 2016 38th Annual International Conference of the IEEE Engineering in …, 2016 | 1 | 2016 |
Slow and Weak Attractor Computation Embedded in Fast and Strong EI Balanced Neural Dynamics X Lin, L Li, B Shi, T Huang, Y Mi, S Wu Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
A Brain-inspired Decision-making Model for Spatio-temporal Pattern Recognition B Wang, B Tan, X Zou, X Lin, C Huang, S Wu, Y Mi 2021 6th IEEE International Conference on Advanced Robotics and Mechatronics …, 2021 | | 2021 |
Fast Learning in Balanced Deep Spiking Neural Networks with Strong and Weak Synapses X Lin, C Wang, B Shi, S Wu | | |
Slow and Weak Attractor Computation Embedded in Fast and Strong EI Balanced Neural Dynamics–Supplementary Information X Lin, L Li, B Shi, T Huang, Y Mi, S Wu | | |