70 citations · 71 across the 2 of their papers we have counts for
3 papers
Proximity Variational Inference
Jaan Altosaar, Rajesh Ranganath, David M. Blei
Variational inference is a powerful approach for approximate posterior inference. However, it is sensitive to initialization and can be subject to poor local optima. In this paper,…
Automatic Differentiation Variational Inference
Alp Kucukelbir, Dustin Tran, Rajesh Ranganath +2
Probabilistic modeling is iterative. A scientist posits a simple model, fits it to her data, refines it according to her analysis, and repeats. However, fitting complex models to l…
Automatic Variational Inference in Stan
Alp Kucukelbir, Rajesh Ranganath, Andrew Gelman +1
Variational inference is a scalable technique for approximate Bayesian inference. Deriving variational inference algorithms requires tedious model-specific calculations; this makes…