70 citations · 70 across the 1 of their papers we have counts for
3 papers
stat.ML2016
Posterior Dispersion Indices
Alp Kucukelbir, David M. Blei
Probabilistic modeling is cyclical: we specify a model, infer its posterior, and evaluate its performance. Evaluation drives the cycle, as we revise our model based on how it perfo…
stat.ML2016
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…
stat.ML2015★ 70 cited
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…