618 citations · 1.9k across the 59 of their papers we have counts for
5 papers · 1 filter
Identifying potentially induced seismicity and assessing statistical significance in Oklahoma and California
Mark McClure, Riley Gibson, Kitkwan Chiu +1
We develop a statistical method for identifying induced seismicity from large datasets and apply the method to decades of wastewater disposal and seismicity data in California and…
Variational Inference via -Upper Bound Minimization
Adji B. Dieng, Dustin Tran, Rajesh Ranganath +2
Variational inference (VI) is widely used as an efficient alternative to Markov chain Monte Carlo. It posits a family of approximating distributions and finds the closest membe…
Operator Variational Inference
Rajesh Ranganath, Jaan Altosaar, Dustin Tran +1
Variational inference is an umbrella term for algorithms which cast Bayesian inference as optimization. Classically, variational inference uses the Kullback-Leibler divergence to d…
Deep Survival Analysis
Rajesh Ranganath, Adler Perotte, Noémie Elhadad +1
The electronic health record (EHR) provides an unprecedented opportunity to build actionable tools to support physicians at the point of care. In this paper, we investigate surviva…
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…