Mixed continous/categorical flow-matching model for de novo molecule generation.

Efficient 3D molecular generation with flow-matching and Semla

MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation

Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c…

Geometric Latent Diffusion Models for 3D Molecule Generation

TorchCFM: a Conditional Flow Matching library

Official code repository for the paper Exploring Chemical Space with Score-based Out-of-distribution Generation (ICML 2023)

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

[NeurIPS 2023] The implementation for the paper "Crystal Structure Prediction by Joint Equivariant Diffusion"

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

Code for “FlowMM Generating Materials with Riemannian Flow Matching” and "FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions"

Open Babel is a chemical toolbox designed to speak the many languages of chemical data.

Code for “From Molecules to Materials Pre-training Large Generalizable Models for Atomic Property Prediction”.

A geometry-complete diffusion generative model (GCDM) for 3D molecule generation and optimization (Nature CommsChem)

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).

A latent text-to-image diffusion model

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

Erasing Concepts from Diffusion Models

RJH Curriculum Vitae

The LaTeX format for my research statement, which has a right figure column

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Heterogeneous Molecular Graph Neural Network

Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.

GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process.

Awesome papers related to generative molecular modeling and design.