A unified framework for machine learning collective variables for enhanced sampling simulations

Molecular mechanics systems and simulation data

Geometric Vector Perceptron --- a rotation-equivariant GNN for learning from biomolecular structure

This Denoising Force Field (DFF) codebase provides a Pytorch framework for the method presented in Two for one: Diffusion models and force fields for coarse-grained molecular dynamics.

Automatic Martini force field generator for small organic molecules (up to 25 heavy atoms), Martini 3 compatible

Create coarse grain Martini input files for Gromacs from (atomistic) pdb files.

A framework for training diffusion models with stable, self-consistent scores near the data distribution.

clash-for-linux

OpenMM tutorial for the MSBS course

End-To-End Molecular Dynamics (MD) Engine using PyTorch

code for "Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching"

Markov Chain Monte Carlo Sampling for Muller Brown Potential

Official PyTorch implementation for "Large Language Diffusion Models"

A deep learning based method for solving high dimensional partial differential equations based on its weak form

Boltzmann Generators and Normalizing Flows in PyTorch

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Code for the paper Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.

A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.

Discrete Flow Matching implemented in PyTorch

Educational implementation of the Discrete Flow Matching paper

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.

Official implementation of Metric Flow Matching (NeurIPS 2024)

code for "Generalized Schrödinger Bridge Matching" (ICLR 2024).

The simplest, fastest repository for training/finetuning medium-sized GPTs.