Bayesian Inference Insights
Rob discusses the challenges of optimizing in high-dimensional parameter spaces and the role of prior information in Bayesian inference. By incorporating historical data on missing rates, models can narrow their search space, leading to more effective solutions. He also shares his current research efforts and encourages academics to cite his work.In this clip
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