Deep neural networks for density functional theory Hamiltonian.

Extended DeepH (xDeepH) method for magnetic materials.

Sparse Gaussian Process Potentials

Open-source first-principles computational toolkit for the efficient calculation of the strength of materials in 1D, 2D, and 3D materials at both zero and finite temperatures

SHRY (Suite for High-throughput generation of models with atomic substitutions implemented by python) is a tool for generating unique ordered structures corresponding to a given disordered structure.

Neural network class for molecular dynamics to predict potential energy, forces and non-adiabatic couplings.

`orbkit` is a JAX-compatible toolkit for continuous ab initio quantum Monte Carlo (QMC) simulations, developed entirely from scratch using Python and JAX.

Python wrappers for TurboRVB

jQMC code implements two real-space ab initio quantum Monte Carlo (QMC) methods. Variatioinal Monte Carlo (VMC) and lattice regularized diffusion Monte Carlo (LRDMC) methods. jQMC achieves high-performance computations especially on GPUs.

Psi4 based Potential energy surface for 1D/2D/4D collisions; TensorFlow (neural networks) Augmenting; Curve Fitting And Multipole Expansion with GUI Interface

Study of molecular motion of Glycerol using NMR modeling and simulations