Causal estimators for use with WhyNot

Overview

WhyNot Estimators

A collection of causal inference estimators implemented in Python and R to pair with the Python causal inference library whynot. For more information, check out the documentation.

Installation

You can perform a minimal installation of whynot_estimators with

git clone https://github.com/zykls/whynot_estimators.git
cd whynot_estimators
pip install -r requirements.txt

You can also install via pip

pip install whynot_estimators

This installs the basic framework. Additional estimators, along with their dependencies are installed separately. To see a list of all available estimators, use

python -m whynot_estimators show_all

To install a particular estimator, e.g. the causal_forest, run

python -m whynot_estimators install causal_forest

Note this estimator requires a working R installation. The show_all command also shows which estimators require R.

To install all of the estimators, use

python -m whynot_estimators install all

Alternatively, you can install the dependencies for a specific estimator by hand by looking here.

Installing R

Some estimators in whynot_estimators require a functioning R installation. One way to satisfy this requirement is using conda.

# Install Anaconda (Linux)
wget https://repo.anaconda.com/archive/Anaconda3-2018.12-Linux-x86_64.sh
bash Anaconda3-2018.12-Linux-x86_64.sh

# Install Anaconda (MacOSx)
wget https://repo.anaconda.com/archive/Anaconda3-2019.03-MacOSX-x86_64.sh
bash Anaconda3-2019.03-MacOSX-x86_64.sh

# Create R environment
conda create --name whynot r-essentials r-base
Owner
ZYKLS
Research groups of Moritz Hardt and Benjamin Recht at UC Berkeley
ZYKLS
《DeepViT: Towards Deeper Vision Transformer》(2021)

DeepViT This repo is the official implementation of "DeepViT: Towards Deeper Vision Transformer". The repo is based on the timm library (https://githu

109 Dec 02, 2022
Code and project page for ICCV 2021 paper "DisUnknown: Distilling Unknown Factors for Disentanglement Learning"

DisUnknown: Distilling Unknown Factors for Disentanglement Learning See introduction on our project page Requirements PyTorch = 1.8.0 torch.linalg.ei

Sitao Xiang 24 May 16, 2022
Python Implementation of the CoronaWarnApp (CWA) Event Registration

Python implementation of the Corona-Warn-App (CWA) Event Registration This is an implementation of the Protocol used to generate event and location QR

MaZderMind 17 Oct 05, 2022
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection, AAAI 2021.

Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection This repository is an official implementation of the AAAI 2021 paper Co-mi

MEGVII Research 20 Dec 07, 2022
POT : Python Optimal Transport

POT: Python Optimal Transport This open source Python library provide several solvers for optimization problems related to Optimal Transport for signa

Python Optimal Transport 1.7k Dec 31, 2022
[ICCV'21] Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

CKDN The official implementation of the ICCV2021 paper "Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment" O

Multimedia Research 50 Dec 13, 2022
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval

More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdh

Ayan Kumar Bhunia 22 Aug 27, 2022
Pytorch implementation of forward and inverse Haar Wavelets 2D

Pytorch implementation of forward and inverse Haar Wavelets 2D

Sergei Belousov 9 Oct 30, 2022
img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation

img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation Figure 1: We estimate the 6DoF rigid transformation of a 3D face (rendered in si

Vítor Albiero 519 Dec 29, 2022
NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

Göktuğ Karakaşlı 16 Dec 05, 2022
How the Deep Q-learning method works and discuss the new ideas that makes the algorithm work

Deep Q-Learning Recommend papers The first step is to read and understand the method that you will implement. It was first introduced in a 2013 paper

1 Jan 25, 2022
Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021

Geometric Vector Perceptron Implementation of Geometric Vector Perceptron, a simple circuit with 3d rotation equivariance for learning over large biom

Phil Wang 59 Nov 24, 2022
MG-GCN: Scalable Multi-GPU GCN Training Framework

MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -

Translational Data Analytics (TDA) Lab @GaTech 6 Oct 24, 2022
Algorithms for outlier, adversarial and drift detection

Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline d

Seldon 1.6k Dec 31, 2022
ArcaneGAN by Alex Spirin

ArcaneGAN by Alex Spirin

Alex 617 Dec 28, 2022
PyTorch Implementation of our paper Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation

PyTorch Implementation of our paper Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation

Zechen Bai 12 Jul 08, 2022
Serving PyTorch 1.0 Models as a Web Server in C++

Serving PyTorch Models in C++ This repository contains various examples to perform inference using PyTorch C++ API. Run git clone https://github.com/W

Onur Kaplan 223 Jan 04, 2023
Visual dialog agents with pre-trained vision-and-language encoders.

Learning Better Visual Dialog Agents with Pretrained Visual-Linguistic Representation Or READ-UP: Referring Expression Agent Dialog with Unified Pretr

7 Oct 08, 2022
An implementation of "Learning human behaviors from motion capture by adversarial imitation"

Merel-MoCap-GAIL An implementation of Merel et al.'s paper on generative adversarial imitation learning (GAIL) using motion capture (MoCap) data: Lear

Yu-Wei Chao 34 Nov 12, 2022
BraTs-VNet - BraTS(Brain Tumour Segmentation) using V-Net

BraTS(Brain Tumour Segmentation) using V-Net This project is an approach to dete

Rituraj Dutta 7 Nov 27, 2022