luigibonati / mlcolvar
A unified framework for machine learning collective variables for enhanced sampling simulations
☆105Updated 2 weeks ago
Alternatives and similar repositories for mlcolvar:
Users that are interested in mlcolvar are comparing it to the libraries listed below
- SO3krates and Universal Pairwise Force Field for Molecular Simulation☆95Updated last week
- ☆63Updated 4 months ago
- AI-enhanced computational chemistry☆80Updated last month
- Reweighted Autoencoded Variational Bayes for Enhanced Sampling (RAVE)☆43Updated 5 years ago
- A Python software package for saddle point optimization and minimization of atomic systems.☆96Updated 6 months ago
- Supporting material for the paper "Data driven collective variables for enhanced sampling"☆18Updated 11 months ago
- train and use graph-based ML models of potential energy surfaces☆90Updated last week
- An open source Python framework for transition interface and path sampling calculations.☆110Updated 3 months ago
- The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules.☆63Updated 3 years ago
- ASH is a Python-based computational chemistry and QM/MM environment, primarily for molecular calculations in the gas phase, explicit sol…☆70Updated this week
- ☆135Updated 7 months ago
- tmQM dataset files☆53Updated last month
- OpenMM plugin to interface with PLUMED☆66Updated 2 months ago
- Martini 3 small-molecule database☆59Updated 8 months ago
- ☆55Updated last month
- ☆43Updated 2 years ago
- Quantum Mechanical Bespoke Force Field Derivation Toolkit☆98Updated 10 months ago
- An object-aware diffusion model for generating chemical reactions☆125Updated 11 months ago
- A Python module for carrying out GCMC insertions and deletions of water molecules in OpenMM.☆67Updated last year
- Atoms In Molecules Neural Network Potential☆103Updated 5 years ago
- Force fields produced by the Open Force Field Initiative☆149Updated 2 weeks ago
- MLP training for molecular systems☆46Updated last week
- Poltype 2: Automated Parameterization for AMOEBA☆45Updated this week
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆72Updated 3 years ago
- Automated tools for the generation of bespoke SMIRNOFF format parameters for individual molecules.☆67Updated this week
- ☆58Updated 3 weeks ago
- Supporting data for the manuscript "Deep learning the slow modes for rare events sampling"☆20Updated 11 months ago
- ☆46Updated 8 months ago
- Efficient And Fully Differentiable Extended Tight-Binding☆87Updated 2 weeks ago
- A collection of Nerual Network Models for chemistry☆123Updated last month