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Conference and Workshop Papers
- 2023
[c6]Félix Chavelli, Zi-Yu Khoo, Jonathan Sze Choong Low, Stéphane Bressan:
Assessing the Effectiveness of Intrinsic Dimension Estimators for Uncovering the Phase Space Dimensionality of Dynamical Systems from State Observations - A Comparative Analysis. DEXA (1) 2023: 259-265- [c5]Zi-Yu Khoo, Abel Yang, Jonathan Sze Choong Low, Stéphane Bressan:
Celestial Machine Learning - From Data to Mars and Beyond with AI Feynman. DEXA (2) 2023: 469-474 - [c4]Zi-Yu Khoo, Jonathan Sze Choong Low, Stéphane Bressan:
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning. iiWAS 2023: 107-120 - [c3]Zi-Yu Khoo, Gokul Rajiv, Abel Yang, Jonathan Sze Choong Low, Stéphane Bressan:
Celestial Machine Learning - Discovering the Planarity, Heliocentricity, and Orbital Equation of Mars with AI Feynman. iiWAS 2023: 201-207 - 2022
- [c2]Zi-Yu Khoo, Delong Zhang, Stéphane Bressan:
What's Next? Predicting Hamiltonian Dynamics from Discrete Observations of a Vector Field. DEXA (2) 2022: 297-302 - 2021
- [c1]Zi-Yu Khoo, Kang Hao Lee
, Zhibo Huang, Stéphane Bressan:
Neural Ordinary Differential Equations for the Regression of Macroeconomics Data Under the Green Solow Model. DEXA (1) 2021: 78-90
Informal and Other Publications
- 2024
- [i7]Yufan Zhu, Zi-Yu Khoo, Jonathan Sze Choong Low, Stéphane Bressan:
A Personalised Learning Tool for Physics Undergraduate Students Built On a Large Language Model for Symbolic Regression. CoRR abs/2407.00065 (2024) - [i6]Félix Chavelli, Zi-Yu Khoo, Dawen Wu, Jonathan Sze Choong Low, Stéphane Bressan:
Physics-informed Discovery of State Variables in Second-Order and Hamiltonian Systems. CoRR abs/2408.11691 (2024) - 2023
- [i5]Zi-Yu Khoo, Jonathan Sze Choong Low, Stéphane Bressan:
Separable Hamiltonian Neural Networks. CoRR abs/2309.01069 (2023) - [i4]Zi-Yu Khoo, Delong Zhang, Stéphane Bressan:
What's Next? Predicting Hamiltonian Dynamics from Discrete Observations of a Vector Field. CoRR abs/2312.08944 (2023) - [i3]Zi-Yu Khoo, Abel Yang, Jonathan Sze Choong Low, Stéphane Bressan:
Celestial Machine Learning: From Data to Mars and Beyond with AI Feynman. CoRR abs/2312.09766 (2023) - [i2]Zi-Yu Khoo, Jonathan Sze Choong Low, Stéphane Bressan:
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning. CoRR abs/2312.09775 (2023) - [i1]Zi-Yu Khoo, Gokul Rajiv, Abel Yang, Jonathan Sze Choong Low, Stéphane Bressan:
Celestial Machine Learning: Discovering the Planarity, Heliocentricity, and Orbital Equation of Mars with AI Feynman. CoRR abs/2312.12315 (2023)
Coauthor Index
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