AI RESEARCH
Bayesian Distributional Models of Executive Functioning
arXiv CS.LG
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ArXi:2510.00387v3 Announce Type: replace This study uses controlled simulations with known ground-truth parameters to evaluate how Distributional Latent Variable Models (DLVM) and Bayesian Distributional Active LEarning (DALE) perform in comparison to conventional Independent Maximum Likelihood Estimation (IMLE). DLVM integrates observations across multiple executive function tasks and individuals, allowing parameter estimation even under sparse or incomplete data conditions.