Pinned Repositories
Active-Learning-Bayesian-Convolutional-Neural-Networks
Active Learning on Image Data using Bayesian ConvNets
AdversarialNetsPapers
The classical papers and codes about generative adversarial nets
aetros-cli
AETROS SDK. Python library to manage/monitor deep learning training in AETROS Trainer
bayesian-belief-networks
Pythonic Bayesian Belief Network Package, supporting creation of and exact inference on Bayesian Belief Networks specified as pure python functions.
bayesian-neural-network-mnist
Bayesian neural network using Pyro and PyTorch on MNIST dataset
BDA_py_demos
Bayesian Data Analysis demos for Python
BDA_R_demos
Bayesian Data Analysis demos for R
blkvar
Package for estimating impacts and cross-site variation in multi-site or blocked RCTs
ExtendingInferences
Code for `Extending inferences from a randomized trial to a new target population'
RCTrep
duolajiang's Repositories
duolajiang/RCTrep
duolajiang/ExtendingInferences
Code for `Extending inferences from a randomized trial to a new target population'
duolajiang/bayesian-neural-network-mnist
Bayesian neural network using Pyro and PyTorch on MNIST dataset
duolajiang/BDA_py_demos
Bayesian Data Analysis demos for Python
duolajiang/BDA_R_demos
Bayesian Data Analysis demos for R
duolajiang/blkvar
Package for estimating impacts and cross-site variation in multi-site or blocked RCTs
duolajiang/CausalInference
CRAN Task View: Causal Inference
duolajiang/contextual
Contextual Bandits in R - simulation and evaluation of Multi-Armed Bandit Policies
duolajiang/denovo
Lee, Small and Dominici (2020) "Discovering Heterogeneous Exposure Effects Using Randomization Inference in Air Pollution Studies"
duolajiang/dgrtwo.github.com
My website
duolajiang/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.
duolajiang/empirical-bayes-book
Introduction to Empirical Bayes: Examples from Baseball Statistics
duolajiang/first
haha
duolajiang/footstrap
Tutorial package
duolajiang/guidelines
Guidelines for publishing a repository in the IKNL space
duolajiang/interpretable-ml-book
Book about interpretable machine learning
duolajiang/IntpTrtRule
duolajiang/Making-accurate-and-interpretable-decisions-for-binary-outcome
duolajiang/Making-accurate-and-interpretable-old-decisions-for-binary-outcome-old
duolajiang/markdown-here
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
duolajiang/mlxtend
A library of extension and helper modules for Python's data analysis and machine learning libraries.
duolajiang/OWRCT_codes_package
Codebase for OW-RCT paper
duolajiang/possum
POSterior SUMmarization
duolajiang/pymatch
duolajiang/python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.
duolajiang/RAOS-Examples
Regression and other stories R examples
duolajiang/sbw
:exclamation: This is a read-only mirror of the CRAN R package repository. sbw — Stable Balancing Weights for Causal Inference and Estimation with Incomplete Outcome Data
duolajiang/TukeySens
R package for sensitivity analysis method in causal inference based on Tukey's Factorization
duolajiang/two-step-framework-causal-effects-validation-simulation
duolajiang/vantage_causalEvaluation