Several Open Books

Publications

See our full publication list on Google Scholar.

Preprints

  1. W.H. Zhang, S. Wu, K. Josić, B. Doiron. Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons, bioRxiv 2022. [Link]

  2. W.H. Zhang, T.S. Lee, B. Doiron, S. Wu, Distributed Sampling-based Bayesian Inference in Coupled Neural Circuits, bioRxiv 2020. [Link]

Featured publications

  1. W.H. Zhang*, Y.N. Wu, S. Wu, "Equivariant Representation in Recurrent Networks with a Continuous Manifold of Attractors". Advances in Neural Information Processing Systems (NeurIPS) 2022. (*Corresponding author)

  2. T. Chu, Z. Ji, J. Zuo, W.H. Zhang, T. Huang, Y. Mi, S, Wu. Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells. Advances in Neural Information Processing Systems (NeurIPS) 2022.

  3. X. Dong, Z. Ji, T. Chu, T. Huang, W.H. Zhang*, Si Wu*. "Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks". Advances in Neural Information Processing Systems (NeurIPS) 2022. (*Corresponding author)

  4. W.H.Zhang, S. Wu, B. Doiron and T.S. Lee, "A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits". Advances in Neural Information Processing Systems (NeurIPS) 2019. [pdf]

  5. W.H. Zhang, H. Wang, A. Chen, Y. Gu, T.S. Lee, K.Y.M. Wong and S. Wu. Complementary Congruent and Opposite Neurons Achieve Concurrent Multisensory Integration and Segregation. eLife (2019). [pdf]

  6. W.H. Zhang, H. Wang, K.Y. Michael Wong and S. Wu. “Congruent” and “Opposite” Neurons: Sisters for Multisensory Integration and Segregation. Advances in Neural Information Processing Systems (NIPS) 2016. [pdf]

  7. W.H. Zhang, A.H. Chen, M. J. Rasch and S. Wu (2016). Decentralized Multisensory Information Integration in Neural Systems. J. Neurosci., 36(2):532-547. [pdf]

  8. S. Wu, K. Y. Michael Wong, C. C. Alan Fung, Y. Mi and W.H. Zhang. Continuous Attractor Neural Networks: Candidate of a Canonical Model for Neural Information Representation. Faculty of 1000, Invitited Review. [pdf]

  9. W.H. Zhang and S. Wu (2013). Reciprocally Coupled Local Estimators Implement Bayesian Information Integration Distributively. Advances in Neural Information Processing Systems (NIPS) 2013. [pdf]

  10. W.H. Zhang and S. Wu (2012). Neural Information Processing with Feedback Modulations. Neural Computation 24(7):1695-1721 [link]

Book Chapter   

  1. W.H. Zhang. Decentralized neural network of multisensory information integration in the brain. Springer. (In Press).