De Novo Molecular Generation with Stacked Adversarial Model. - Yuansan Liu; James Bailey 001 (AI, 2022)

Pandemic model with data-driven phase detection, a study using COVID-19 data. - Yuansan Liu; Saransh Srivastava; Zuo Huang; Felisa J. Vázquez-Abad (J. Oper. Res. Soc., 2023)

Time Series Representation Learning with Supervised Contrastive Temporal Transformer. - Yuansan Liu; Sudanthi N. R. Wijewickrema; Christofer Bester; Stephen J. O'Leary; James Bailey 001 (IJCNN, 2024)

Time-Transformer: Integrating Local and Global Features for Better Time Series Generation. - Yuansan Liu; Sudanthi N. R. Wijewickrema; Ang Li; Christofer Bester; Stephen J. O'Leary; James Bailey 001 (SDM, 2024)

Bidirectional Adversarial Autoencoders for the design of Plasmonic Metasurfaces. - Yuansan Liu; Jeygopi Panisilvam; Peter M. Dower; Sejeong Kim; James Bailey 001 (CoRR, 2024)

Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting. - Yuansan Liu; Sudanthi N. R. Wijewickrema; Dongting Hu; Christofer Bester; Stephen J. O'Leary; James Bailey 001 (CoRR, 2024)

Probabilistic and Neural Modelling for Time Series Analysis. - Yuansan Liu (2024)

Artificial Intelligence Assurance in Head and Neck Surgery: Now and Next. - Yuansan Liu; Sudanthi N. R. Wijewickrema; Bridget Copson; Jean-Marc Gerard; Sameer Antani (CBMS, 2025)