244 citations · 2.6k across the 44 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…
Discrete Flows: Invertible Generative Models of Discrete Data
Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal +2
While normalizing flows have led to significant advances in modeling high-dimensional continuous distributions, their applicability to discrete distributions remains unknown. In th…
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…