m-k-S / awesome-machine-learning-atomistic-simulationLinks
An overview of literature that discusses the use of machine learning for atomistic simulations
☆45Updated 2 years ago
Alternatives and similar repositories for awesome-machine-learning-atomistic-simulation
Users that are interested in awesome-machine-learning-atomistic-simulation are comparing it to the libraries listed below
Sorting:
- Deep Modeling for Molecular Simulation, two-day virtual workshop, July 7-8, 2022☆53Updated 3 years ago
- Training Neural Network potentials through customizable routines in JAX.☆59Updated 4 months ago
- The architector python package - for 3D metal complex design. C22085☆75Updated 3 weeks ago
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆41Updated last year
- Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.☆38Updated 2 years ago
- This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.☆19Updated 3 years ago
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆36Updated last year
- Generate and predict molecular electron densities with Euclidean Neural Networks☆49Updated 2 years ago
- ☆35Updated 3 months ago
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆27Updated 2 years ago
- A Newtonian message passing network for deep learning of interatomic potentials and forces☆45Updated 6 months ago
- The Wren sits on its Roost in the Aviary.☆61Updated 2 months ago
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Updated last month
- Official implementation of DeepDFT model☆85Updated 2 years ago
- An ecosystem for digital reticular chemistry☆52Updated last year
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆82Updated 3 years ago
- A Reinforcement Framework for Inverse Design of MOFs☆34Updated last year
- Moment Invariants Local Atomic Descriptor☆34Updated last year
- Predict the electronic structure and atomic properties (potential energy, forces, and stress tensor) of polymers containing N and/or O.☆22Updated last year
- Alchemical machine learning interatomic potentials☆32Updated last year
- Equivariant network to predict activation barriers and molecular orbitals through coefficients of molecular orbitals.☆12Updated last year
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆21Updated last year
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆38Updated last year
- ⚛ download and manipulate atomistic datasets☆48Updated last month
- A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.☆45Updated last year
- Machine learning exercises for the MolSim course (http://www.acmm.nl/molsim/molsim2023/index.html)☆28Updated last year
- Deprecated - see `pair_nequip_allegro`☆44Updated 8 months ago
- open data sets for machine learning pertaining to porous materials☆27Updated 2 years ago
- UF3: a python library for generating ultra-fast interatomic potentials☆68Updated 6 months ago
- ☆32Updated 2 months ago