117 citations · 1.1k across the 40 of their papers we have counts for
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Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimension
Sergei Manzhos, Manabu Ihara
Kernel methods such as kernel ridge regression and Gaussian process regressions with Matern type kernels have been increasingly used, in particular, to fit potential energy surface…
Machine learning of kinetic energy densities with target and feature averaging: better results with fewer training data
Sergei Manzhos, Johann Lüder, Manabu Ihara
Machine learning of kinetic energy functionals (KEF), in particular kinetic energy density (KED) functionals, has recently attracted attention as a promising way to construct KEFs…
Atoms, dimers, and nanoparticles from orbital-free density-potential functional theory
Martin-Isbjörn Trappe, William C. Witt, Sergei Manzhos
Density-potential functional theory (DPFT) is an alternative formulation of orbital-free density functional theory that may be suitable for modeling the electronic structure of lar…
Orders-of-coupling representation with a single neural network with optimal neuron activation functions and without nonlinear parameter optimization
Sergei Manzhos, Manabu Ihara
Representations of multivariate functions with low-dimensional functions that depend on subsets of original coordinates (corresponding of different orders of coupling) are useful i…
Neural network with optimal neuron activation functions based on additive Gaussian process regression
Sergei Manzhos, Manabu Ihara
Feed-forward neural networks (NN) are a staple machine learning method widely used in many areas of science and technology. While even a single-hidden layer NN is a universal appro…