Manabu Ihara

Orcid: 0000-0002-3397-1378

According to our database1, Manabu Ihara authored at least 8 papers between 2021 and 2023.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2023
Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimension.
CoRR, 2023

Orders-of-coupling representation with a single neural network with optimal neuron activation functions and without nonlinear parameter optimization.
CoRR, 2023

Neural network with optimal neuron activation functions based on additive Gaussian process regression.
CoRR, 2023

2022
Easy representation of multivariate functions with low-dimensional terms via Gaussian process regression kernel design: applications to machine learning of potential energy surfaces and kinetic energy densities from sparse data.
Mach. Learn. Sci. Technol., 2022

Random Sampling High Dimensional Model Representation Gaussian Process Regression (RS-HDMR-GPR) for representing multidimensional functions with machine-learned lower-dimensional terms allowing insight with a general method.
Comput. Phys. Commun., 2022

The loss of the property of locality of the kernel in high-dimensional Gaussian process regression on the example of the fitting of molecular potential energy surfaces.
CoRR, 2022

2021
Rectangularization of Gaussian process regression for optimization of hyperparameters.
CoRR, 2021

On the optimization of hyperparameters in Gaussian process regression.
CoRR, 2021


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