Comparing Three Data Representations for Music with a Sequence-to-Sequence Model. - Sichao Li; Charles Patrick Martin (Australasian Conference on Artificial Intelligence, 2020)

Optimization-Free Inverse Design of High-Dimensional Nanoparticle Electrocatalysts Using Multi-target Machine Learning. - Sichao Li; Jonathan Y. C. Ting; Amanda S. Barnard (ICCS (1), 2022)

Variance Tolerance Factors For Interpreting Neural Networks. - Sichao Li; Amanda S. Barnard (CoRR, 2022)

The impact of domain-driven and data-driven feature selection on the inverse design of nanoparticle catalysts. - Sichao Li; Jonathan Y. C. Ting; Amanda S. Barnard (J. Comput. Sci., 2022)

Variance Tolerance Factors For Interpreting All Neural Networks. - Sichao Li; Amanda S. Barnard (IJCNN, 2023)

Simultaneous prediction of hand gestures, handedness, and hand keypoints using thermal images. - Sichao Li; Sean Banerjee; Natasha Kholgade Banerjee; Soumyabrata Dey (CoRR, 2023)

Exploring the cloud of feature interaction scores in a Rashomon set. - Sichao Li; Rong Wang; Quanling Deng; Amanda S. Barnard (ICLR, 2024)

Diverse Explanations from Data-driven and Domain-driven Perspectives for Machine Learning Models. - Sichao Li; Amanda S. Barnard (CoRR, 2024)

Automated architectural space layout planning using a physics-inspired generative design framework. - Zhipeng Li; Sichao Li; Geoff Hinchcliffe; Noam Maitless; Nick Birbilis (CoRR, 2024)

Practical Attribution Guidance for Rashomon Sets. - Sichao Li; Amanda S. Barnard; Quanling Deng (CoRR, 2024)

EXAGREE: Towards Explanation Agreement in Explainable Machine Learning. - Sichao Li; Quanling Deng; Amanda S. Barnard (CoRR, 2024)

Diverse explanations from data-driven and domain-driven perspectives in the physical sciences. - Sichao Li; Xin Wang; Amanda S. Barnard (Mach. Learn. Sci. Technol., 2025)