2017 (modified: 14 May 2023)ICML 2017Readers: Everyone
Abstract: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 performs. This require...