| Continuous attractor neural networks: candidate of a canonical model for neural information representation S Wu, KYM Wong, CCA Fung, Y Mi, WH Zhang F1000Research 5, 2016 | 72 | 2016 |
| Decentralized multisensory information integration in neural systems WH Zhang, A Chen, MJ Rasch, S Wu Journal of Neuroscience 36 (2), 532-547, 2016 | 69 | 2016 |
| Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation WH Zhang, H Wang, A Chen, Y Gu, TS Lee, KYM Wong, S Wu eLife 8, e43753, 2019 | 40 | 2019 |
| Surfgen: Adversarial 3d shape synthesis with explicit surface discriminators A Luo, T Li, WH Zhang, TS Lee Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 33 | 2021 |
| 25th annual computational neuroscience meeting: CNS-2016 TO Sharpee, A Destexhe, M Kawato, V Sekulić, FK Skinner, DK Wójcik, ... BMC neuroscience 17, 1-112, 2016 | 27 | 2016 |
| Neural information processing with feedback modulations WH Zhang, S Wu Neural computation 24 (7), 1695-1721, 2012 | 22 | 2012 |
| Dynamic information encoding with dynamic synapses in neural adaptation L Li, Y Mi, WH Zhang, DH Wang, S Wu Frontiers in Computational Neuroscience 12, 16, 2018 | 16 | 2018 |
| Firing rate adaptation affords place cell theta sweeps, phase precession, and procession T Chu, Z Ji, J Zuo, Y Mi, W Zhang, T Huang, D Bush, N Burgess, S Wu Elife 12, RP87055, 2024 | 13 | 2024 |
| Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons WH Zhang, S Wu, K Josić, B Doiron Nature communications 14 (1), 7074, 2023 | 11 | 2023 |
| A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits WH Zhang, S Wu, B Doiron, TS Lee Advances in Neural Information Processing Systems, 3799-3808, 2019 | 11 | 2019 |
| “Congruent” and “opposite” neurons: sisters for multisensory integration and segregation WH Zhang, H Wang, KY Wong, S Wu Advances in Neural Information Processing Systems 29, 2016 | 10 | 2016 |
| Reciprocally coupled local estimators implement Bayesian information integration distributively WH Zhang, S Wu Advances in Neural Information Processing Systems, 19-27, 2013 | 10 | 2013 |
| Conformal isometry of lie group representation in recurrent network of grid cells D Xu, R Gao, WH Zhang, XX Wei, YN Wu arXiv preprint arXiv:2210.02684, 2022 | 9 | 2022 |
| Distributed sampling-based Bayesian inference in coupled neural circuits WH Zhang, TS Lee, B Doiron, S Wu bioRxiv, 2020.07. 20.212126, 2020 | 9 | 2020 |
| Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks X Dong, Z Ji, T Chu, T Huang, S Wu, WH Zhang Advances in Neural Information Processing Systems, 2022 | 8 | 2022 |
| Translation-equivariant Representation in Recurrent Networks with a Continuous Manifold of Attractors WH Zhang, YN Wu, S Wu Advances in Neural Information Processing Systems, 2022 | 6 | 2022 |
| How the prior information shapes neural networks for optimal multisensory integration H Wang, WH Zhang, KYM Wong, S Wu Advances in Neural Networks-ISNN 2017: 14th International Symposium, ISNN …, 2017 | 5 | 2017 |
| Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells T Chu, Z Ji, J Zuo, WH Zhang, T Huang, Y Mi, S Wu Advances in Neural Information Processing Systems, 2022 | 4 | 2022 |
| Representational geometries reveal differential effects of response correlations on population codes in neurophysiology and functional magnetic resonance imaging ZJ Cheng, L Yang, WH Zhang, RY Zhang Journal of Neuroscience 43 (24), 4498-4512, 2023 | 3 | 2023 |
| The dynamics of bimodular continuous attractor neural networks with static and moving stimuli M Yan, WH Zhang, H Wang, KYM Wong arXiv: 1910.07263, 2019 | 2 | 2019 |
Si WuPeking UniversityBestätigte E-Mail-Adresse bei pku.edu.cn
