Stars
All Algorithms implemented in Python
You like pytorch? You like micrograd? You love tinygrad! ❤️
Machine Learning Engineering Open Book
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
A debugging and profiling tool that can trace and visualize python code execution
ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.
Schedule-Free Optimization in PyTorch
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Implementation of Alphafold 3 from Google Deepmind in Pytorch
High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
Toolbox for molecular animations in Blender, powered by Geometry Nodes.
Self-contained, minimalistic implementation of diffusion models with Pytorch.
User friendly and accurate binder design pipeline
Visualisations of data are at the core of every publication of scientific research results. They have to be as clear as possible to facilitate the communication of research. As data can have differ…
A generative model for programmable protein design
A clean, three-column Sphinx theme with Bootstrap for the PyData community
Generation of protein sequences and evolutionary alignments via discrete diffusion models
Central repository for biomolecular foundation models with shared trainers and pipeline components
A py.test plugin to validate Jupyter notebooks
Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"
A generalized computational framework for biomolecular modeling.
Plausibility checks for generated molecule poses.
Joint sequence and structure generation with RoseTTAFold sequence space diffusion
Official implementation of All Atom Diffusion Transformers (ICML 2025)
Protein hallucination and inpainting with RoseTTAFold
Benchmarking framework for protein representation learning. Includes a large number of pre-training and downstream task datasets, models and training/task utilities. (ICLR 2024)