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Jun Dai
Jun Dai
Postdoc, Mila - Quebec AI Institute
Verified email at mila.quebec
Title
Cited by
Cited by
Year
Interpolation and extrapolation of global potential energy surfaces for polyatomic systems by Gaussian processes with composite kernels
J Dai, RV Krems
Journal of Chemical Theory and Computation 16 (3), 1386-1395, 2020
432020
Machine learning corrected quantum dynamics calculations
A Jasinski, J Montaner, RC Forrey, BH Yang, PC Stancil, N Balakrishnan, ...
Physical Review Research 2 (3), 032051, 2020
182020
Quantum Gaussian process model of potential energy surface for a polyatomic molecule
J Dai, RV Krems
The Journal of Chemical Physics 156 (18), 2022
72022
Neural network Gaussian processes as efficient models of potential energy surfaces for polyatomic molecules
J Dai, RV Krems
Machine Learning: Science and Technology 4 (4), 045027, 2023
22023
Benchmarking of quantum fidelity kernels for Gaussian process regression
X Guo, J Dai, RV Krems
arXiv preprint arXiv:2407.15961, 2024
2024
Applications of classical and quantum machine learning for quantum problems
J Dai
University of British Columbia, 2023
2023
Gausian processes for system-agnostic construction of high-dimensional PES with sparse ab initio data
J Dai, H Sugisawa, T Ida, R Krems
APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts 2020 …, 2020
2020
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