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Fast Non-autoregressive Inverse Folding with Discrete Diffusion (NeurIPS MLSB 2023)
The main features of johnyang101/pmpnndiff are: Diffusion Models.
Open-source alternatives to johnyang101/pmpnndiff include: lucidrains/denoising-diffusion-pytorch — Implementation of Denoising Diffusion Probabilistic Model in Pytorch. tencent-ailab/ip-adapter — IP-Adapter is a framework for conditioning pretrained text-to-image diffusion models to use image prompts as visual… google-deepmind/alphafold3 — AlphaFold3 is a biomolecular structure prediction model and bioinformatics structural analysis tool. It uses a deep… datawhalechina/tiny-universe — Tiny Universe is an educational monorepo that delivers multiple independent implementations of core AI subsystems as… lamm-mit/proteindiffusiongenerator — Reference: B. Ni, D.L. Kaplan, M.J. Buehler, Generative design of de novo proteins based on secondary structure… liuyf020419/scuba-d — SCUBA-D: De novo protein design with a denoising diffusion network independent of pre-trained structure prediction…
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
IP-Adapter is a framework for conditioning pretrained text-to-image diffusion models to use image prompts as visual guides. It serves as a text-to-image model extension that transforms a text-based diffusion model to accept and process image inputs as primary generation sources. The system implements identity preservation to maintain consistent facial features across multiple outputs using a reference photo. It also enables style transfer workflows to produce image variations that preserve the artistic characteristics of a source image. Capabilities cover multi-modal prompting, including the
AlphaFold3 is a biomolecular structure prediction model and bioinformatics structural analysis tool. It uses a deep learning system to predict the three-dimensional shapes of proteins, DNA, RNA, and ligands. The system functions as a diffusion-based protein folding model that predicts the spatial coordinates of biomolecular atoms and interactions. It utilizes a GPU-accelerated inference pipeline to process genetic sequences and structural templates for molecular modeling. The project covers structural bioinformatics analysis and protein interaction modeling to determine the physical arrangem
Tiny Universe is an educational monorepo that delivers multiple independent implementations of core AI subsystems as self-contained Jupyter notebooks. It provides from-scratch constructions of foundational architectures including a complete Transformer model built from the original paper specification, a denoising diffusion probabilistic model for image generation, and a ReAct-style autonomous agent framework that equips an LLM with tools for planning and multi-step task execution. The project distinguishes itself by covering the full lifecycle of modern AI systems through hands-on implementa