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Challenges and Opportunities in High-dimensional Variational Inference
Our framework and supporting experiments help to distinguish between the behavior of BBVI methods for approximating low-dimensional versus moderate-to-high-dimensional posteriors.
Independent finite approximations for Bayesian nonparametric inference
We call our construction the automated independent finite approximation (AIFA).
Reconstructing probabilistic trees of cellular differentiation from single-cell RNA-seq data
Specifically, we extend the framework of the classical Dirichlet diffusion tree to simultaneously infer branch topology and latent cell states along continuous trajectories over the full tree.
Fast robustness quantification with variational Bayes
Bayesian hierarchical models are increasing popular in economics.
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