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Deep learning quantum Monte Carlo for electrons in real space
User friendly, flexible and extensible object-oriented Fortran unit testing framework for testing serial, MPI-parallelized and coarray-parallelized applications
Reference implementation of "Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions" (ICLR, 2022) and "Sampling-free Inference ob Ab-Initio Potential Energy Surface Networks…
NequIP is a code for building E(3)-equivariant interatomic potentials
A library for symmetry operations and linear interpolation within an irreducible part of the first Brillouin zone.
Proposal for an exception handling mechanism in Fortran with a new syntax and corresponding equivalent implementation in Fortran 2008.
A modular framework for neural networks with Euclidean symmetry
Pytorch implementation of KFAC - this is a port of https://github.com/tensorflow/kfac/
auto-formatter for modern fortran source code
An implementation of the Fermionic Neural Network for ab-initio electronic structure calculations
Pytorch Implementation of Real Space Quantum Monte Carlo Simulations of Molecular Systems
Data and scripts for comprehensive benchmark of conformer relative energies
Python library for real space quantum Monte Carlo
Quantum chemistry program executor and IO standardizer (QCSchema).
Gaussian-Processes Surrogate Optimisation in python
⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.
TorchANI 2.0 is an open-source library that supports training, development, and research of ANI-style neural network interatomic potentials. It was originally developed and is currently maintained …