430 citations · 768 across the 15 of their papers we have counts for
3 papers · 1 filter
Analyzing the Role of Model Uncertainty for Electronic Health Records
Michael W. Dusenberry, Dustin Tran, Edward Choi +5
In medicine, both ethical and monetary costs of incorrect predictions can be significant, and the complexity of the problems often necessitates increasingly complex models. Recent…
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles
Charles Weill, Javier Gonzalvo, Vitaly Kuznetsov +9
AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for automatically learning high-quality ensembles with minimal expert intervention. Our framework is inspire…
Measuring Calibration in Deep Learning
Jeremy Nixon, Mike Dusenberry, Ghassen Jerfel +4
Overconfidence and underconfidence in machine learning classifiers is measured by calibration: the degree to which the probabilities predicted for each class match the accuracy of…