We review progress in neural network (NN)-based methods for the construction of
interatomic potentials from discrete samples (such as ab initio energies) for applications in …

Surrogate models are popular tool to approximate the functional relationship of expensive
simulation models in multiple scientific and engineering disciplines. Successful use of …

The integration of optimization methodologies with computational analyses/simulations has
a profound impact on the product design. Such integration, however, faces multiple …

Development and applications of neural network (NN)‐based approaches for representing
potential energy surfaces (PES) of bound and reactive molecular systems are reviewed …

We combine the high dimensional model representation (HDMR) idea of Rabitz and co-
workers [J. Phys. Chem. 110, 2474 (2006)] with neural network (NN) fits to obtain an …

Computational tools such as finite element analysis and simulation are widely used in
engineering, but they are mostly used for design analysis and validation. If these tools can …

High dimensional model representation is under active development as a set of quantitative
model assessment and analysis tools for capturing high-dimensional input− output system …

Abstract The High Dimensional Model Representation (HDMR) technique decomposes an n-
variate function f (x) into a finite hierarchical expansion of component functions in terms of …

Quantum-dynamical full-dimensional (15D) calculations are reported for the protonated
water dimer (H 5 O 2+) using the multiconfiguration time-dependent Hartree (MCTDH) …

We present an approach combining a representation of a multivariate function using
subdimensional functions with machine learning based representation of component …