Highlighted MSc thesis: Scalable Inference for Crossed Random Effects Models

Recent MSc thesis about performance improvements of Cholesky decomposition focusing on sparse cases.
Random effects models

On a method to improve scalability of problems including Cholesky decomposition with expected sparsity. One of the highlighted BGSE projects, from one of our last cohort students (MSc Data Science), Maximilian Müller, under the supervision of Omiros Papaspiliopoulos.

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