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stat.ME2024
Bayesian ICA with super-Gaussian Source Priors
Jyotishka Datta, Soham Ghosh, Nicholas G. Polson
Independent Component Analysis (ICA) plays a central role in modern machine learning as a flexible framework for feature extraction. We introduce a horseshoe-type prior with a late…
stat.ME2024★ 1 cited
Pochhammer Priors for Sparse Count Models
Yuexi Wang, Nicholas G. Polson
Bayesian hierarchical models are commonly employed for inference in count datasets, as they account for multiple levels of variation by incorporating prior distributions for parame…