Yuhang Liu

Dr Yuhang Liu

Postdoc

Australian Institute for Machine Learning - Projects

Faculty of Sciences, Engineering and Technology

My current major research topics are about:

  1. building the bridge between causality and machine learning, e.g., causal representation learning, multi domain/modal Learning;

  2. building the bridge between Bayesian learning and deep learning, e.g., Bayesian deep learning and deep Bayesian learning;

  3. inverse problems in various applications, e.g., computer vision, signal processing.

Homepage: https://sites.google.com/view/yuhangliu/homepage

  • Journals
    Year Citation
    2024 Yan, Q., Wang, H., Ma, Y., Liu, Y., Dong, W., Woźniak, M., & Zhang, Y. (2024). Uncertainty estimation in HDR imaging with Bayesian neural networks. Pattern Recognition, 156, 110802.
    DOI
    2020 Wen, S., Deng, L., & Liu, Y. (2020). Distributed optimization via primal and dual decompositions for delay-constrained FANETs. Ad Hoc Networks, 109, 1-14.
    DOI Scopus12
    2018 Liu, Y., Dong, W., & Zhou, M. (2018). Frame-Based Variational Bayesian Learning for Independent or Dependent Source Separation. IEEE Transactions on Neural Networks and Learning Systems, 29(10), 4983-4996.
    DOI Scopus11
    2016 Dong, W. Y., Kang, L. L., Liu, Y. H., & Li, K. S. (2016). Opposition-based particle swarm optimization with adaptive elite mutation and nonlinear inertia weight. Tongxin Xuebao/Journal on Communications, 37(12), 1-10.
    DOI Scopus19
  • Position: Postdoc
  • Email: yuhang.liu01@adelaide.edu.au
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning
  • Org Unit: Australian Institute for Machine Learning - Operations
Connect With Me
External Profiles