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Sara Wade is a Reader in the School of Mathematics at the University of Edinburgh, specializing in Bayesian nonparametrics and machine learning. With extensive research in mixture models, clustering, and dimension reduction techniques, she employs advanced statistical methods such as Dirichlet processes and Gaussian processes. Her work includes the use of MCMC and variational inference approaches, contributing to the field’s understanding of complex data structures. Sara has published numerous papers and continues to engage in collaborative research to further develop innovative methodologies in statistical analysis.
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