selected publications

  1. Song, J., Yuan, Y.*, Chang, K., Xu, B., Xuan, J. and Pang, W., 2024. Navigating Public Sentiment in the Circular Economy through Topic Modelling and Hyperparameter Optimisation. submitted to Energy and AI journal.
  2. Yuan, Y., Wang, W., Li, X., Chen, K., Yonghan, Z. and Pang, W., 2024. Evolving Molecular Graph Neural Networks with Hierarchical Evaluation Strategy. Genetic and Evolutionary Computation Conference (GECCO) 2024.
  3. Song, J., Yuan, Y.* and Pang, W., 2024. SAIS: A Novel Bio-Inspired Artificial Immune System Based on Symbiotic Paradigm. Genetic and Evolutionary Computation Conference (GECCO) Workshop 2024.
  4. Yuan, Y.*, Yang, Z.*, Xu, Y.*, Zhan, S., Bai, H. and Chen, K., 2023. FACE: Evaluating Natural Language Generation with Fourier Analysis of Cross-Entropy. Thirty-seventh Conference on Neural Information Processing Systems (NIPS 2023).
  5. Hasan, S. and Yuan, Y., 2023. Minority Ethnic Vulnerabilities in the Use of Digital Housing Services Across Age Groups. European Network for Housing Research.
  6. Yang, Z., Bai, H., Luo, Z., Xu, Y., Pang, W., Wang, Y., Yuan, Y. and Yuan, Y. (corresponding author), 2023. PaCaNet: A study on cyclegan with transfer learning for diversifying fused chinese painting and calligraphy. arXiv preprint arXiv:2301.13082.
  7. Yuan, Y., Wang, W. and Pang, W., 2021, July. Which hyperparameters to optimise? an investigation of evolutionary hyperparameter optimisation in graph neural network for molecular property prediction. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Companion (pp. 1403-1404).
  8. Yuan, Y., Wang, W. and Pang, W., 2021, June. A genetic algorithm with tree-structured mutation for hyperparameter optimisation of graph neural networks. In 2021 IEEE Congress on Evolutionary Computation (CEC) (pp. 482-489). IEEE.
  9. Yuan, Y., Wang, W. and Pang, W., 2021, June. A systematic comparison study on hyperparameter optimisation of graph neural networks for molecular property prediction. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 386-394).
  10. Wang, W., Moreau, N.G., Yuan, Y., Race, P.R. and Pang, W., 2019. Towards machine learning approaches for predicting the self-healing efficiency of materials. Computational Materials Science, 168, pp.180-187.