A unified framework for machine learning collective variables for enhanced sampling simulations
☆145Sep 24, 2026Updated this week
Alternatives and similar repositories for mlcolvar
Users that are interested in mlcolvar are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Supporting data for the manuscript "Deep learning the slow modes for rare events sampling"☆23Jun 6, 2024Updated 2 years ago
- Supporting material for the paper "Data driven collective variables for enhanced sampling"☆22Jun 6, 2024Updated 2 years ago
- Development version of plumed 2☆517Updated this week
- ML potentials via transfer learning☆30Updated this week
- LASP python library including scripts and auto-NNtrain workflow☆20Nov 16, 2023Updated 2 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Data efficient active learning for machine learning potentials☆19Jul 31, 2026Updated last month
- MCMC-based algorithm for sampling surface reconstructions☆46Mar 1, 2026Updated 6 months ago
- Package for reading, analysis and visualization of metadynamics HILLS☆41Nov 28, 2023Updated 2 years ago
- ☆61Sep 16, 2026Updated last week
- A Python package for estimating diffusion properties from molecular dynamics simulations.☆88Sep 7, 2026Updated 2 weeks ago
- 基于python的PLUMED的可视化界面开发☆14Jan 8, 2025Updated last year
- ☆15Mar 3, 2025Updated last year
- DMFF (Differentiable Molecular Force Field) is a Jax-based python package that provides a full differentiable implementation of molecular…☆199Jul 21, 2026Updated 2 months ago
- ☆26Jun 16, 2025Updated last year
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Deep Coarse-grained Potentials via Relative Entropy Minimization☆18Feb 22, 2023Updated 3 years ago
- A simple implementation of replica exchange MD simulations for OpenMM.☆27Jul 19, 2021Updated 5 years ago
- Training Neural Network potentials through customizable routines in JAX.☆73Updated this week
- ☆140May 3, 2026Updated 4 months ago
- MatID is a Python package for identifying and analyzing atomistic systems based on their structure.☆14Jul 6, 2026Updated 2 months ago
- Accelerating Metadynamics-Based Free-Energy Calculations with Adaptive Machine Learning Potentials☆18Jun 9, 2021Updated 5 years ago
- Compute neighbor lists for atomistic systems☆85Sep 10, 2026Updated 2 weeks ago
- To run metadynamics simulations using openMM (based on Peter Eastman's script)☆13Mar 18, 2019Updated 7 years ago
- Python package for efficient analysis of HILLS files generated by Plumed metadynamics simulations. Inspired by the Metadynminer package f…☆22Feb 2, 2026Updated 7 months ago
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- Run OpenMM with forces provided by any Python program☆42Dec 25, 2024Updated last year
- An open-source Python package for creating fast and accurate interatomic potentials.☆362Updated this week
- ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.☆159Jun 27, 2024Updated 2 years ago
- MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.☆1,360Updated this week
- An automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials☆23Jun 6, 2026Updated 3 months ago
- ☆13Jul 17, 2025Updated last year
- Torch-native, batchable, atomistic simulations.☆496Updated this week
- Example to fit parameters and run CG simulations using TorchMD and Schnet☆48Feb 4, 2022Updated 4 years ago
- MLP training for molecular systems☆61Sep 18, 2026Updated last week
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov☆412Sep 15, 2026Updated last week
- PENSA - a collection of python methods for exploratory analysis and comparison of biomolecular conformational ensembles.☆153Feb 12, 2025Updated last year
- ☆68Dec 9, 2024Updated last year
- Atomistic machine learning models you can use everywhere for everything☆49Updated this week
- Quick Uncertainty and Entropy via STructural Similarity☆67Apr 1, 2026Updated 5 months ago
- Collective variables library for molecular simulation and analysis programs☆243Updated this week
- Set of tools for input preparation for conserved water search from MD trajectories (gromacs, amber) and their analysis☆20Sep 17, 2026Updated last week