It is well known that standard frequentist inference breaks down in IV regressions with weak instruments. Bayesian inference with diffuse priors suffers from the same problem. We show that the issue ...
This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...
Citation Lee, Clarence. "User Adaptive Web Morphing: An Implementation of a Web-based Bayesian Inference Engine with Gittins Index: Master of Engineering Thesis." Massachusetts Institute of Technology ...
This paper is a generalization of earlier studies by Ferreira (1975) and Holbert and Broemeling (1977), who used improper prior distributions in order to make informal Bayesian inferences for the ...
(Nanowerk News) How can the component elements of an unknown material, such as a meteorite, be determined? X-ray fluorescence analysis can be used to identify an abundance of elements, by irradiating ...
A new technical paper titled “Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks” was published by researchers at Université Grenoble Alpes, CEA, ...
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