DiffSBDD
OpenChem
DiffSBDD | OpenChem | |
---|---|---|
1 | 1 | |
290 | 657 | |
- | - | |
4.9 | 0.0 | |
8 months ago | 5 months ago | |
Python | Python | |
MIT License | MIT License |
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DiffSBDD
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Learn diffusion models with Hugging Face course 🧨
I'm referring to recent works like DiffLinker (https://github.com/igashov/DiffLinker) and DiffSBDD (https://github.com/arneschneuing/diffsbdd) which use diffusion to generate new ligands or fragments of molecules. If there's enough interest, we could find space to include these exciting topics in the course :)
OpenChem
What are some alternatives?
minimal-text-diffusion - A minimal implementation of diffusion models for text generation
NeuralCDE - Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
DiffLinker - DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design
chemicalx - A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
DDPM_inversion - Official pytorch implementation of the paper: "An Edit Friendly DDPM Noise Space: Inversion and Manipulations". CVPR 2024.
pixel - Research code for pixel-based encoders of language (PIXEL)
DenoisingDiffusionProbabilityModel-ddpm- - This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.
Clairvoyante - Clairvoyante: a multi-task convolutional deep neural network for variant calling in Single Molecule Sequencing