1 code implementation • 7 May 2024 • Yuansan Liu, Jeygopi Panisilvam, Peter Dower, Sejeong Kim, James Bailey
An example of this is the design of photonic metasurfaces by using their photoluminescent spectrum as the input data to predict their topology.
1 code implementation • 16 Mar 2024 • Yuansan Liu, Sudanthi Wijewickrema, Christofer Bester, Stephen O'Leary, James Bailey
We show that the model performs with high reliability and efficiency on the online CPD problem ($\sim$98\% and $\sim$97\% area under precision-recall curve respectively).
1 code implementation • 18 Dec 2023 • Yuansan Liu, Sudanthi Wijewickrema, Ang Li, Christofer Bester, Stephen O'Leary, James Bailey
Experimental results demonstrate that our model can outperform existing state-of-the-art models in 5 out of 6 datasets, specifically on those with data containing both global and local properties.
no code implementations • 24 Oct 2021 • Yuansan Liu, Saransh Srivastava, Zuo Huang, Felisa J. Vázquez-Abad
The main contributions of our model are: (a) providing interpretation of the parameters, (b) determining which parameters of the model are more important to produce changes in the spread of the disease, and (c) using data-driven discovery of sudden changes in the evolution of the pandemic.
no code implementations • 24 Oct 2021 • Yuansan Liu, James Bailey
A second stage model then takes these features to learn properties of the molecules and refine more valid molecules.