inverse-propensity-scoring

Here are 2 public repositories matching this topic...

bagheri365 / PolicyRecLab

A research lab for off-policy evaluation, exploration, and policy-generated bias in contextual-bandit recommendation systems.

recommender-systems causal-inference importance-sampling contextual-bandits exploration-exploitation selection-bias counterfactual-learning off-policy-evaluation doubly-robust inverse-propensity-scoring

Updated Sep 9, 2026
Python

Off policy evaluation audit for logged bandits: measures how much of a target policy's probability mass sits outside what the log could have produced, shows that a 95 percent interval around the standard estimator covers 0.26 of the time, and returns exit 2 rather than a number when the estimate would be about a different quantity.

python numpy ci-cd recommender-systems causal-inference model-validation importance-sampling contextual-bandits mlops github-actions off-policy-evaluation doubly-robust ml-evaluation counterfactual-evaluation inverse-propensity-scoring

Updated Aug 26, 2026
Python

Add this topic to your repo

To associate your repository with the inverse-propensity-scoring topic, visit your repo's landing page and select "manage topics."

Learn more

Navigation Menu

inverse-propensity-scoring

Here are 2 public repositories matching this topic...

bagheri365 / PolicyRecLab

srujan20 / offpolicy-gap

Add this topic to your repo