1 citations · 2 across the 6 of their papers we have counts for
9 papers
A fast summation method for the DFT-D3 dispersion correction
Victoria Valeeva, Cheuk Hin Ho, Mario Geiger +4
The DFT-D3 dispersion correction is routinely added to machine learning force fields (MLFFs) trained on dispersion-deficient functionals such as PBE. Its environment-dependent pair…
Equivariant Many-body Message Passing Interatomic Potentials for Magnetic Materials
Cheuk Hin Ho, Cas van der Oord, James P. Darby +11
Magnetism governs key properties of materials used in energy, data storage, and spintronic technologies, yet its complex coupling to lattice and electronic degrees of freedom chall…
Stochastic Reconfiguration with Warm-Started SVD
Dexuan Zhou, Huajie Chen, Cheuk Hin Ho +2
The combination of the variational Monte Carlo (VMC) method with deep learning wave function architectures has led to several successes in ground-state calculations of quantum many…
Variational Geometry-aware Neural Network based Method for Solving High-dimensional Diffeomorphic Mapping Problems
Zhiwen Li, Cheuk Hin Ho, Lok Ming Lui
Traditional methods for high-dimensional diffeomorphic mapping often struggle with the curse of dimensionality. We propose a mesh-free learning framework designed for -dimension…
Flexible Uncertainty Calibration for Machine-Learned Interatomic Potentials
Cheuk Hin Ho, Christoph Ortner, Yangshuai Wang
Reliable uncertainty quantification (UQ) is essential for developing machine-learned interatomic potentials (MLIPs) in predictive atomistic simulations. Conformal prediction (CP) i…
A Conformal Prediction Framework for Uncertainty Quantification in Physics-Informed Neural Networks
Yifan Yu, Cheuk Hin Ho, Yangshuai Wang
Physics-Informed Neural Networks (PINNs) have emerged as a powerful framework for solving PDEs, yet existing uncertainty quantification (UQ) approaches for PINNs generally lack rig…
Atomic Cluster Expansion without Self-Interaction
Cheuk Hin Ho, Timon S. Gutleb, Christoph Ortner
The Atomic Cluster Expansion (ACE) (Drautz, Phys. Rev. B 99, 2019) has been widely applied in high energy physics, quantum mechanics and atomistic modeling to construct many-body i…
ACEpotentials.jl: A Julia Implementation of the Atomic Cluster Expansion
William C. Witt, Cas van der Oord, Elena Gelžinytė +10
We introduce ACEpotentials.jl, a Julia-language software package that constructs interatomic potentials from quantum mechanical reference data using the Atomic Cluster Expansion (D…
A Multilevel Method for Many-Electron Schrödinger Equations Based on the Atomic Cluster Expansion
Dexuan Zhou, Huajie Chen, Cheuk Hin Ho +1
The atomic cluster expansion (ACE) (Drautz, 2019) yields a highly efficient and intepretable parameterisation of symmetric polynomials that has achieved great success in modelling…