An experimental language for causal reasoning

Deep universal probabilistic programming with Python and PyTorch

A library for bayesian variable selection

Rewriting the Stan compiler in OCaml

Python interface for the Stan to (Num)Pyro compiler.

Bayesian Regression Models in Pyro

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Low-code framework for building custom LLMs, neural networks, and other AI models

Functional tensors for probabilistic programming

A Bayesian latent tree model of high-dimensional heterogeneous data

Lanugage of Thought (LOT) models in Python.

A tool to automatically generate pseudo-code from source code.

Cool links & research papers related to Machine Learning applied to source code (MLonCode)

A library that uses hardware acceleration to load sequences of video frames to facilitate machine learning training

Compiler for Neural Network hardware accelerators

A highly efficient implementation of Gaussian Processes in PyTorch

TensorLy: Tensor Learning in Python.

Write PyTorch code at the level of individual examples, then run it efficiently on minibatches.

Handle the piping between Python and Unity. Helpers for ML in Python (PyTorch, Tensorflow, Pyro/Edward) as well as C# classes for quick domain construction.

Probabilistic reasoning and statistical analysis in TensorFlow

A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.

Bayesian Optimization using GPflow

Invent abstract functions using anti-unification.

Python AST that abstracts the underlying Python version

This is a suite of reinforcement learning environments illustrating various safety properties of intelligent agents.

Cornell House Agent Learning Environment

Jupyter kernel for Racket

A Python implementation for Racket

Tools for loading standard data sets in machine learning