The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...
Quantum designers: Florian Marquardt (left) and Leopoldo Sarra have shown how deep Bayesian experimental design can be applied to quantum many-body systems. (Courtesy: Leopoldo Sarra) As quantum ...
A problem of interest for ecology and conservation is that of determining the best allocation of survey effort in studies aimed at estimating the proportion of sites occupied by a species. Many ...
Evaluation of the HER/PI3K/AKT Family Signaling Network as a Predictive Biomarker of Pathologic Complete Response for Patients With Breast Cancer Treated With Neratinib in the I-SPY 2 TRIAL BaSyc is ...
Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...
Bayesian Information Design and Mechanism Optimization is an interdisciplinary field that synthesises insights from economics, statistics, and game theory to address challenges of asymmetric ...
Since variance components are nonlinear parameters in a linear model, classical optimal designs for estimating variance components in the one-way random effects model depend on the values of the ...
Description: Bayesian and decision theoretic formulation of problems; construction of utility functions and quantifications of prior information; methods of Bayesian decision and inference, with ...
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