Bayesian approaches to variable selection and model comparison construct a coherent probabilistic framework that integrates prior beliefs with observed data. In variable selection, each candidate ...
Learning in dynamic and stochastic environments is notoriously difficult. Neuromodulatory systems may shape this process, thereby constraining where learning-related neu ...
A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...
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