neildhir

rebound

💫 An open-source multi-purpose N-body code.

pyOMT

A PyTorch implementation of adaptive Monte Carlo Optimal Transport algorithm

GPJax

Gaussian processes in JAX.

bqtorch

An implementation of Bayesian Quadrature based on GPytorch

bayesian-quadrature

Bayesian quadrature

cid-latex

Latex package for drawing (causal) influence diagrams (CIDs) and labeling incentives, maintained by the Causal Incentives Working Group

gpytorch

A highly efficient implementation of Gaussian Processes in PyTorch

GRAPL

GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference

causaleffect

Python package to compute conditional and non-conditional causal effects.

y0

❓y0 (pronounced "why not?") is for causal inference in Python

annotate-equations

LaTeX package and annotated examples for annotating equations using TikZ.

annotated_latex_equations

Examples of how to create colorful, annotated equations in Latex using Tikz.

open-interpreter

A natural language interface for computers

dagsim

A framework and specification language for simulating data based on graphical models

Awesome-Uplift-Model

🛠 How to Apply Causal ML to Real Scene Modeling？How to learn Causal ML？【✔从Causal ML到实际场景的Uplift建模】

csplib

A benchmark library for constraints

bolei_awesome_posters

CVPR and NeurIPS poster examples and templates. May we have in-person poster session soon!

mathematics-roadmap

A Comprehensive Roadmap to Mathematics

PyTorch-VAE

A Collection of Variational Autoencoders (VAE) in PyTorch.

neuromancer

Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

gpf

A Fortran library for Gaussian process regression

MO-ASMOCH

bo_pr

Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization

MVMOO

Mixed Variable Multi-Objective Optimisation

oyster

Oyster is a Python package for performing causal inference using causal diagrams.

ananke

Ananke named for the Greek primordial goddess of necessity and causality, is a python package for causal inference using the language of graphical models., import from https://gitlab.com/causal/ananke

dosearch

dosearch: R Package for Identifying General Causal Queries

whynot

A Python sandbox for decision making in dynamics

awesome-causality-algorithms

An index of algorithms for learning causality with data

causal-inference-cheat-sheet

Summary of useful results in Causal Inference