Materials informatics. - Seeram Ramakrishna; Tong-Yi Zhang; Wen-Cong Lu; Quan Qian; Jonathan Sze Choong Low; Jeremy Heiarii Ronald Yune; Daren Zong Loong Tan; Stéphane Bressan; Stefano Sanvito; Surya R. Kalidindi (J. Intell. Manuf., 2019)

Assessing the Effectiveness of Intrinsic Dimension Estimators for Uncovering the Phase Space Dimensionality of Dynamical Systems from State Observations - A Comparative Analysis. - Félix Chavelli; Zi-Yu Khoo; Jonathan Sze Choong Low; Stéphane Bressan (DEXA (1), 2023)

Celestial Machine Learning - From Data to Mars and Beyond with AI Feynman. - Zi-Yu Khoo; Abel Yang; Jonathan Sze Choong Low; Stéphane Bressan (DEXA (2), 2023)

A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning. - Zi-Yu Khoo; Jonathan Sze Choong Low; Stéphane Bressan (iiWAS, 2023)

Celestial Machine Learning - Discovering the Planarity, Heliocentricity, and Orbital Equation of Mars with AI Feynman. - Zi-Yu Khoo; Gokul Rajiv; Abel Yang; Jonathan Sze Choong Low; Stéphane Bressan (iiWAS, 2023)

Separable Hamiltonian Neural Networks. - Zi-Yu Khoo; Jonathan Sze Choong Low; Stéphane Bressan (CoRR, 2023)

A Personalised Learning Tool for Physics Undergraduate Students Built On a Large Language Model for Symbolic Regression. - Yufan Zhu; Zi-Yu Khoo; Jonathan Sze Choong Low; Stéphane Bressan (CoRR, 2024)

Physics-Informed Discovery of State Variables in Second-Order and Hamiltonian Systems. - Félix Chavelli; Zi-Yu Khoo; Dawen Wu; Jonathan Sze Choong Low; Stéphane Bressan (ACIIDS (1), 2025)

Periodic Hamiltonian Neural Networks. - Zi-Yu Khoo; Dawen Wu; Jonathan Sze Choong Low; Stéphane Bressan (IEEE Trans. Artif. Intell., 2025)