luigibonati / data-driven-CVsLinks
Supporting material for the paper "Data driven collective variables for enhanced sampling"
☆19Updated last year
Alternatives and similar repositories for data-driven-CVs
Users that are interested in data-driven-CVs are comparing it to the libraries listed below
Sorting:
- Rethinking Metadynamics: From Bias Potentials to Probability Distributions☆12Updated last year
- MLP training for molecular systems☆49Updated this week
- AI-enhanced computational chemistry☆100Updated last month
- A unified framework for machine learning collective variables for enhanced sampling simulations☆116Updated this week
- ☆71Updated 7 months ago
- MACE-OFF23 models☆42Updated 6 months ago
- PSP is a python toolkit for predicting atomic-level structural models for a range of polymer geometries.☆43Updated last year
- Martini 3 small-molecule database☆62Updated 11 months ago
- A python implementation of the string method with swarms of trajectories using GROMACS☆18Updated 2 years ago
- Material for the 3rd i-CoMSE Workshop: Methods for Advanced Sampling☆41Updated 2 years ago
- ☆47Updated 3 years ago
- Reweighted Autoencoded Variational Bayes for Enhanced Sampling (RAVE)☆43Updated 5 years ago
- Repository of the data for PLUMED Masterclass 22.3☆14Updated last year
- Descriptors-free Collective Variables From Geometric Graph Neural Networks.☆11Updated 7 months ago
- ☆59Updated 2 months ago
- tmQM dataset files☆53Updated 4 months ago
- rule-based virtual polymer library generator☆41Updated 2 weeks ago
- ☆31Updated 2 weeks ago
- Tutorials of few enhanced sampling methods along with bash script to run the method in a single shot..☆48Updated 4 years ago
- Machine learning exercises for the MolSim course (http://www.acmm.nl/molsim/molsim2023/index.html)☆27Updated last year
- Ionic liquid force field parameters (OPLS-2009IL and OPLS-VSIL)☆64Updated 11 months ago
- A comprehensive tool for analyzing liquid solvation structure.☆53Updated last week
- “Ab initio thermodynamics of liquid and solid water” Bingqing Cheng, Edgar A. Engel, JÖrg Behler, Christoph Dellago and Michele Ceriotti…☆27Updated 5 years ago
- AIMNet-NSE model☆45Updated last year
- An automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials☆20Updated last month
- Example scripts using the CSD Python API☆75Updated last week
- The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for organic molecules.☆64Updated 3 years ago
- ☆41Updated 3 weeks ago
- This is a simple but efficient implementation of PaiNN-model for constructing machine learning interatomic potentials☆21Updated 2 years ago
- A package for all physics based/related models☆53Updated 10 months ago