We review the role of self-consistency in density functional theory (DFT). We apply a recent
analysis to both Kohn–Sham and orbital-free DFT, as well as to partition DFT, which …

Brain-predicted age difference scores are calculated by subtracting chronological age from
'brain'age, which is estimated using neuroimaging data. Positive scores reflect accelerated …

Using a one-dimensional model, we explore the ability of machine learning to approximate
the non-interacting kinetic energy density functional of diatomics. This nonlinear …

Accurate approximations to density functionals have recently been obtained via machine
learning (ML). By applying ML to a simple function of one variable without any random …

Methodologies for multidimensionality reduction aim at discovering low-dimensional
manifolds where data ranges. Principal Component Analysis (PCA) is very effective if data …

Idealized first-principles models of chemical plants can be inaccurate. An alternative is to fit
a Machine Learning (ML) model directly to plant sensor data. We use a structured approach …

The Kohn-Sham scheme of density functional theory is one of the most widely used methods
to solve electronic structure problems for a vast variety of atomistic systems across different …

Idealized first-principles models of chemical plants can be inaccurate. An alternative is to fit
a Machine Learning (ML) model directly to plant sensor data. We use a structured approach …

Speaker adaptation is implemented in order to shift the speaker-independent model closer
to the new speaker speech characteristics to improve the speech recognition performance …

Computation and simulation play a central role in physics. As applied to atoms, molecules,
and condensed-matter systems, this is based on quantum mechanics. Many calculations are …