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bcauss

Code for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"

covid19-sounds-kdd20

dragonnet-pytorch

pytorch implementation of dragonnet

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 in

flexible-losses-for-binary-classification-with-gbdt

Gradient statistics for implementing a generalized hybrid loss function in gradient-boosted decision trees (GBDT) for binary classification tasks.

gbrt-for-tsf

gluonts

Probabilistic time series modeling in Python

lightgbmlss

An extension of LightGBM to probabilistic forecasting

local-causal-discovery

Code for the paper "Local Causal Discovery for Estimating Causal Effects".

pytorch-transformer-ts

Repository of Transformer based PyTorch Time Series Models

reliabledosagecombi

Implementation of "Reliable Off-Policy Learning for Dosage Combinations"

rieszlearning

Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests"