《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

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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