Conformal Off-policy Prediction
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Updated
Feb 9, 2023 - R
Conformal Off-policy Prediction
Implementation of "A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes" (ICML)
Implementation of "Off-Policy Interval Estimation with Confounded Markov Decision Process" (JASA, 2022+)
Implementation of "A Reinforcement Learning Framework for Dynamic Mediation Analysis" (ICML 2023) in Python.
HOPES: HVAC optimization with Off-Policy Evaluation and Selection
Implementation of Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings (NeurIPS, 2021) in Python
Omitting-States-Irrelevant-to-Return Importance Sampling estimator for off-policy evaluation
[NeurIPS 2023] Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation. https://arxiv.org/abs/2310.17146
On the Reuse Bias in Off-Policy Reinforcement Learning (IJCAI 2023)
Implementation of "Deeply-Debiased Off-Policy Interval Estimation" (ICML, 2021) in Python
Stateful implementations of OPE algorithms, designed for use in the development of offline RL models
(NeurIPS2023) "Future-Dependent Value-Based Off-Policy Evaluation in POMDPs"
Robust Offline Reinforcement Learning with Heavy-Tailed Rewards
Off-Policy Interval Estimation withConfounded Markov Decision Process
Representation Learning for OPE
(KDD2023) "Off-Policy Evaluation of Ranking Policies under Diverse User Behavior"
(WSDM2022 Best Paper Award Runner-Up) "Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model"
Reinforcement Learning Short Course
SCOPE-RL: A python library for offline reinforcement learning, off-policy evaluation, and selection
Implementations and examples of common offline policy evaluation methods in Python.
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