The Next Platform

Using Bayesian Inference To Reverse Engineer Decades Of HPC

A collaboration including the University of Oxford, University of British Columbia, Intel, New York University, CERN, and the National Energy Research Scientific Computing Center is working to make it ...
JSTOR Daily

Learning from a lot: Empirical Bayes for high-dimensional model-based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
JSTOR Daily

BAYESIAN NONPARAMETRIC INFERENCE ON THE STIEFEL MANIFOLD

The Stiefel manifold Vp,d is the space of all d × p orthonormal matrices, with the d−1 hypersphere and the space of all orthogonal matrices constituting special cases. In modeling data lying on the ...
Diginomica

Growing better brains - why we need to re-think the neuron for more trustworthy and efficient AI

Verses demonstrates progress in leveraging AI models using Bayesian networks and active inference that are significantly smaller, more energy efficient, and honest than Deep Neural Network approaches.
International Monetary Fund

Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited ...
lse

Bayesian Inference

This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Data Science, BSc in Mathematics with Data Science, BSc in Mathematics with Economics ...
lse

Bayesian Machine Learning

This course is available on the MSc in Applied Social Data Science, MSc in Data Science, MSc in Econometrics and Mathematical Economics, MSc in Health Data Science, MSc in Operations Research & ...