samanbanafti
Ph.D. candidate at the University of California, Riverside working on econometrics.
University of California, Riverside Riverside, CA
Pinned Repositories
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.
causalForest
DEPRECATED. See new generalized random forest package for up-to-date implementation.
demand_forecast
gluon-ts
Probabilistic time series modeling in Python
grf
Generalized Random Forests
leebounds
Better Lee Bounds
mixup-cifar10
mixup: Beyond Empirical Risk Minimization
samanbanafti's Repositories
samanbanafti/causalForest
DEPRECATED. See new generalized random forest package for up-to-date implementation.
samanbanafti/demand_forecast
samanbanafti/gluon-ts
Probabilistic time series modeling in Python
samanbanafti/grf
Generalized Random Forests
samanbanafti/leebounds
Better Lee Bounds
samanbanafti/mixup-cifar10
mixup: Beyond Empirical Risk Minimization