Alejandro's repositories
Applied-Deep-Learning
Applied Deep Learning
AtomicGraphNets.jl
Atomic graph models for molecules and crystals in Julia
cgdms
Differentiable molecular simulation of proteins with a coarse-grained potential
cgmap
Simple fine-grained to coarse-grained molecular dynamics mapping code
cgnet
learning coarse-grained force fields
cookiecutter-cms
Python-centric Cookiecutter for Molecular Computational Chemistry Packages
Learning-DL
Python implementations to learn DL
MESO
USER-MESO package for LAMMPS
NeuralForceField
Neural Network Force Field based on PyTorch
Physics-Based-Deep-Learning
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond
VerySimpleMD
A very simple molecular dynamics code
openpathsampling
An open source Python framework for transition interface and path sampling calculations.
papers-for-molecular-design-using-DL
List of molecular design using Generative AI and Deep Learning
PySAGES
Python Suite for Advanced General Ensemble Simulations
schnax
An implementation of SchNet in JAX and JAX-MD.
torchmd-cg
Example to fit parameters and run CG simulations using TorchMD and Schnet
torchmd-net
Neural network potentials based on graph neural networks and equivariant transformers
USER-3SPN2
Coarse-grained molecular model of DNA (LAMMPS plugin)
warp
A Python framework for high performance GPU simulation and graphics