125 citations · 1.2k across the 71 of their papers we have counts for
73 papers
The Curious Case of the Default Settings: Evaluating Default Performance of Variational Inference Software
Madelyn Andersen, Elizabeth Bersson, Tamara Broderick
We systematically evaluate a suite of off-the-shelf variational inference (VI) software packages from the perspective of a standard practitioner. Using simple analytic benchmark mo…
The Bayesian Infinitesimal Jackknife for Variance
Ryan Giordano, Tamara Broderick
The frequentist variability of Bayesian posterior expectations can provide meaningful measures of uncertainty even when models are misspecified. Classical methods to asymptotically…
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box
Ryan Giordano, Martin Ingram, Tamara Broderick
Automatic differentiation variational inference (ADVI) offers fast and easy-to-use posterior approximation in multiple modern probabilistic programming languages. However, its stoc…
Evaluating Sensitivity to the Stick-Breaking Prior in Bayesian Nonparametrics (Rejoinder)
Ryan Giordano, Runjing Liu, Michael I. Jordan +1
One can typically form a local robustness metric for a particular problem quite directly, for Markov chain Monte Carlo applications as well as optimization problems such as variati…
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
Renato Berlinghieri, Brian L. Trippe, David R. Burt +5
Given sparse observations of buoy velocities, oceanographers are interested in reconstructing ocean currents away from the buoys and identifying divergences in a current vector fie…
Are you using test log-likelihood correctly?
Sameer K. Deshpande, Soumya Ghosh, Tin D. Nguyen +1
Test log-likelihood is commonly used to compare different models of the same data or different approximate inference algorithms for fitting the same probabilistic model. We present…