We study the problem of estimating the distribution of the return of a policy using an offline
dataset that is not generated from the policy, ie, distributional offline policy evaluation (OPE) …

This paper introduces SCOPE-RL, a comprehensive open-source Python software designed
for offline reinforcement learning (offline RL), off-policy evaluation (OPE), and selection …

Estimation of the Average Treatment Effect (ATE) is a core problem in causal inference with
strong connections to Off-Policy Evaluation in Reinforcement Learning. This paper considers …

The estimation of cumulative distribution functions (CDFs) is an important learning task with
a great variety of downstream applications, such as risk assessments in predictions and …

Estimating cumulative distribution functions (CDFs) of context-dependent random variables
is a central statistical task underpinning numerous applications in machine learning and …

Taking the current PPP governance in China as the research object, this paper explores the
governance structure and the role of institutional governance. Grounded theory is used in …