Quantum chemistry uses quantum mechanics for the first-principle exploration of chemical systems. In principle, all chemical phenomena can be studied by solving the Schrödinger equation, the ...

Researchers found that the Gaussian Process Regression (GPR) machine learning model is the most reliable tool for forecasting ...

Partial differential equation (PDE) models of physical systems with initial and boundary conditions are often solved numerically via a computer code called the simulator. To study the dependence of ...

We revisit the problem of determining the sample size for a Gaussian process emulator and provide a data analytic tool for exact sample size calculations that goes beyond the n = 10d rule of thumb and ...

GPR works well with small datasets and generates a metric of confidence of a predicted result, but it's moderately complex and the results are not easily interpretable, says Dr. James McCaffrey of ...

Gaussian process regression is a sophisticated technique that uses what is called the kernel trick to deal with complex non-linear data, and L2 regularization to avoid model overfitting where a model ...