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@chem-gp

Chem-GP

Chemical Discovery with Probabilistic ML
README.md

Fitting molecular Energies, Forces and Chemical shifts with scalable Gaussian Processes by Stochastic Variational Inference

Current scope of the project is focused on the following applications:

  • molecular dynamics
  • averaging of chemical shifts
  • chemical reaction network discovery

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Pinned

  1. fande fande Public

    Fitting molecular Energies, Forces and Chemical shifts and Chemical Discovery with Scalable Gaussian Processes by Stochastic Variational Inference

    Python 2 1

Repositories

Showing 8 of 8 repositories
  • fande Public

    Fitting molecular Energies, Forces and Chemical shifts and Chemical Discovery with Scalable Gaussian Processes by Stochastic Variational Inference

    Python 2 MIT 1 0 0 Updated Mar 6, 2024
  • artificial-rotors Public

    Artificial force rotations for fast sampling of the rotational energy profiles of molecular systems by structure optimization and molecular dynamics

    0 0 0 0 Updated Feb 22, 2024
  • librascal Public Forked from lab-cosmo/librascal

    A scalable and versatile library to generate representations for atomic-scale learning

    C++ 0 LGPL-2.1 20 0 0 Updated Jul 3, 2023
  • i-pi Public Forked from i-pi/i-pi

    i-PI: a universal force engine

    Python 0 111 0 0 Updated May 12, 2023
  • pw-benchmarks Public

    Benchmark studies for the plane wave calculations

    Python 0 MIT 0 0 0 Updated Mar 10, 2023
  • saddle-dynamics Public

    GP-aided saddle-point molecular dynamics

    Jupyter Notebook 0 MIT 2 1 0 Updated Oct 18, 2022
  • .github Public
    0 0 0 0 Updated Oct 14, 2022
  • examples Public
    Jupyter Notebook 0 MIT 0 0 0 Updated Jun 6, 2022

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