xwbxxx's Stars
shap/shap
A game theoretic approach to explain the output of any machine learning model.
py-why/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
rguo12/awesome-causality-algorithms
An index of algorithms for learning causality with data
Curt-Park/rainbow-is-all-you-need
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow
jakobrunge/tigramite
Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at
Petterpx/FloatingX
Android上强大的悬浮窗组件,支持 系统浮窗(需要权限)、应用内浮窗(无权限)、局部悬浮(View),支持边缘吸附、回弹、自定义动画、位置保存、窗口化及分屏后位置修复等。Android without permission suspension window(App), support global(View), local suspension, support edge adsorption, rebound, custom animation, position saving, windowing and split-screen position repair.
NotGlop/docker-drag
Download image from the Docker Hub HTTPS API
cmu-phil/tetrad
Repository for the Tetrad Project, www.phil.cmu.edu/tetrad.
Renovamen/pcalg-py
Implement PC algorithm in Python | PC 算法的 Python 实现
dreamhomes/TroubleShooter
The algorithms about root cause analysis/localization/diagnosis in AIOps.
dreamhomes/PCIC-2021-Track1
PCIC 2021 Track1: Causal Discovery
xiangyu-sun-789/NTS-NOTEARS
Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
giovanniMen/CPCaD-Bench
Continuous Industrial Process datasets for benchmarking Causal Discovery methods
Amber-Yes-We-Code/leap
LEAP is a novel tool for discovering latent temporal causal relations.
JiaYaobo/stamox
make your statistical research faster
ckassaad/PCGCE
csquires/dct-policy
dimitri-G/Business_Application
dimitri-G/KFLServlet
dimitri-G/pplication
test
xwbxxx/ZJU_SummerSchool_ProjectTemplate