1k citations · 5.3k across the 132 of their papers we have counts for
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Hybrid Variational/Gibbs Collapsed Inference in Topic Models
Max Welling, Yee Whye Teh, Hilbert Kappen
Variational Bayesian inference and (collapsed) Gibbs sampling are the two important classes of inference algorithms for Bayesian networks. Both have their advantages and disadvanta…
On Smoothing and Inference for Topic Models
Arthur Asuncion, Max Welling, Padhraic Smyth +1
Latent Dirichlet analysis, or topic modeling, is a flexible latent variable framework for modeling high-dimensional sparse count data. Various learning algorithms have been develop…
Bayesian Rose Trees
Charles Blundell, Yee Whye Teh, Katherine A. Heller
Hierarchical structure is ubiquitous in data across many domains. There are many hierarchical clustering methods, frequently used by domain experts, which strive to discover this s…