13 citations · 13 across the 4 of their papers we have counts for
4 papers
Extending Causal Metamodeling to a non-Markovian Queue
Pracheta Amaranath, Anant Bhide, David Jensen +1
Metamodels for discrete-event simulations approximate the behavior of simulation models without running expensive simulations. Prior work introduced modular dynamic Bayesian networ…
Improving Generative Methods for Causal Evaluation via Simulation-Based Inference
Pracheta Amaranath, Vinitra Muralikrishnan, Amit Sharma +1
Generating synthetic datasets that accurately reflect real-world observational data is critical for evaluating causal estimators, but it remains a challenging task. Existing genera…
Adaptive Selection of the Optimal Strategy to Improve Precision and Power in Randomized Trials
Laura B. Balzer, Erica Cai, Lucas Godoy Garraza +1
Benkeser et al. demonstrate how adjustment for baseline covariates in randomized trials can meaningfully improve precision for a variety of outcome types. Their findings build on a…
Measuring Interventional Robustness in Reinforcement Learning
Katherine Avery, Jack Kenney, Pracheta Amaranath +2
Recent work in reinforcement learning has focused on several characteristics of learned policies that go beyond maximizing reward. These properties include fairness, explainability…