Stars
An extremely fast Python package and project manager, written in Rust.
Official implementation of the NeurIPS 24 paper of statistical flow matching (SFM) for discrete generation.
Convert jax functions to sympy for symbolic analysis. This is useful for sparsity detection.
Inference code for scalable emulation of protein equilibrium ensembles with generative deep learning
Just another minimalist Jekyll theme which designed for technical writing blog.
Efficient 3D molecular generation with flow-matching and Semla
List of papers studying machine learning through the lens of category theory
Bare-bones implementations of some generative models in Jax: diffusion, normalizing flows, consistency models, flow matching, (beta)-VAEs, etc
Pythonic AI generation of images and videos
Experiments with artificial neural networks and geodesy
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Lean 3's obsolete mathematical components library: please use mathlib4
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Optax is a gradient processing and optimization library for JAX.
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
Pytorch framework for doing deep learning on point clouds.
Examples in Python about plotting and interpolating a B-spline curve and their comparison using Numpy, Scipy and Matplotlib.
Deep representation of interplanetary trajectories
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
A PyTorch library for building deep reinforcement learning agents.
Dubin's car planning challenge in pure Python.
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations