1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ME2026
Deep adaptive design with an evidential bias criterion
David Chen, Michael Evans, Xinwei Li +2
Bayesian optimal experimental design (BOED) aims to collect informative data by optimizing an expected utility reflecting the goals of an experiment. However, this optimization is…
stat.ME2024
Multi-objective Bayesian optimization for Likelihood-Free inference in sequential sampling models of decision making
David Chen, Xinwei Li, Eui-Jin Kim +2
Statistical models are often defined by a generative process for simulating synthetic data, but this can lead to intractable likelihoods. Likelihood free inference (LFI) methods en…
stat.CO2023★ 1 cited
concrete: Targeted Estimation of Survival and Competing Risks in Continuous Time
David Chen, Helene C. W. Rytgaard, Edwin C. H. Fong +4
This article introduces the R package concrete, which implements a recently developed targeted maximum likelihood estimator (TMLE) for the cause-specific absolute risks of time-to-…