Oral
Yes, but Did It Work?: Evaluating Variational Inference
Yuling Yao · Aki Vehtari · Daniel Simpson · Andrew Gelman

Wed Jul 11th 05:00 -- 05:20 PM @ A4

While it's always possible to compute a variational approximation to a posterior distribution, it can be difficult to discover problems with this approximation". We propose two diagnostic algorithms to alleviate this problem. The Pareto-smoothed importance sampling (PSIS) diagnostic gives a goodness of fit measurement for joint distributions, while simultaneously improving the error in the estimate. The variational simulation-based calibration (VSBC) assesses the average performance of point estimates.

Author Information

Yuling Yao (Columbia University)
Aki Vehtari (Aalto University)
Daniel Simpson (University of Toronto)
Andrew Gelman (Columbia University)

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