learningmatter-mit / Coarse-Graining-Auto-encodersLinks
☆21Updated 6 years ago
Alternatives and similar repositories for Coarse-Graining-Auto-encoders
Users that are interested in Coarse-Graining-Auto-encoders are comparing it to the libraries listed below
Sorting:
- Example to fit parameters and run CG simulations using TorchMD and Schnet☆48Updated 3 years ago
- Geometric super-resolution for molecular geometries☆42Updated 3 years ago
- Machine learning predictions of bond dissociation energy☆64Updated last year
- Supporting data for the manuscript "Deep learning the slow modes for rare events sampling"☆21Updated last year
- Message Passing Neural Networks for Molecule Property Prediction☆47Updated 3 years ago
- learning coarse-grained force fields☆64Updated 3 years ago
- Implementation of "Denoise Pretraining on Non-equilibrium Molecular Conformations for Accurate and Transferable Neural Potentials" in PyT…☆14Updated 2 years ago
- Implicit Solvent Approach Based on Generalised Born and Transferable Graph Neural Networks for Molecular Dynamics Simulations☆50Updated 6 months ago
- Keras layers for end-to-end learning with rdkit and pymatgen☆61Updated last year
- Learning Molecular Dynamics with Simple Language Model built upon Long Short-Term Memory Neural Network☆43Updated 3 years ago
- Graph-based genetic algorithm☆92Updated 4 years ago
- Force field-inspired molecular representation learning model☆21Updated 2 years ago
- Unified Free Energy Dynamics (UFED) simulations with OpenMM☆35Updated 3 months ago
- An E(3) Equivariant Variational Autoencoder for Molecular Linker Design☆49Updated 3 years ago
- Tutorials and data necessary to reproduce the results of publication Machine Learning Coarse-Grained Potentials of Protein Thermodynamics☆90Updated 9 months ago
- Code for the paper "JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design"☆86Updated 3 years ago
- Supplementary Data for "A graph representation of molecular ensembles for polymer property prediction"☆21Updated 3 years ago
- Accelerated sampling framework with autoencoder-based method☆23Updated 6 years ago
- Denoising diffusion probabilistic models for replica exchange☆24Updated 3 years ago
- G-SchNet extension for SchNetPack☆62Updated last week
- TrajCast: Force-Free MD Through Autoregressive Equivariant Networks☆56Updated last month
- Implementation of Differentiable Molecular Simulations with torchMD.☆15Updated 2 years ago
- cG-SchNet - a conditional generative neural network for 3d molecular structures☆62Updated 2 years ago
- G-SchNet - a generative model for 3d molecular structures☆144Updated 2 years ago
- Automatic Martini force field generator for small organic molecules (up to 25 heavy atoms), Martini 3 compatible☆26Updated 4 months ago
- Reweighted Autoencoded Variational Bayes for Enhanced Sampling (RAVE)☆44Updated 5 years ago
- A machine learned Molecular Mechanics force field with integration into GROMACS and OpenMM☆55Updated last week
- Molecular Dynamic Graph Neural Network☆20Updated 4 years ago
- Using supervised machine learning to build collective variables for accelerated sampling☆28Updated 7 years ago
- Equivariant GNN for the prediction of atomic multipoles up to quadrupoles.☆30Updated 3 years ago