《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新，English version in translation

Pytorch implementation of convolutional neural network visualization techniques

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

A trainable PyTorch reproduction of AlphaFold 3.

A summary of related works about flow matching, stochastic interpolants

A curated list of resources about generative flow networks (GFlowNets).

Software Design by Example: a tool-based introduction with Python

Ankh: Optimized Protein Language Model

Protein structure datasets for machine learning.

Code repository for Trajectory Flow Matching

GflowNets, MCMC, Metropolis-Hasting, Gibbs sampling, Metropolis-adjusted Langevin, Inverse Transform Sampling, Acceptance-Rejection Method and Important Sampling

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

Benchmarks for moscot

StructureFlow: Simulation-free Structure Learning for Stochastic Dynamics