What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?
This work aims to develop a measure that can accurately rank the performance of various
classifiers when they are tested on unlabeled data from out-of-distribution (OOD) …
classifiers when they are tested on unlabeled data from out-of-distribution (OOD) …
Great models think alike: Improving model reliability via inter-model latent agreement
Reliable application of machine learning is of primary importance to the practical
deployment of deep learning methods. A fundamental challenge is that models are often …
deployment of deep learning methods. A fundamental challenge is that models are often …
Assessing Model Out-of-distribution Generalization with Softmax Prediction Probability Baselines and A Correlation Method
This paper studies the use of Softmax prediction to assess model generalization under
distribution shift. Specifically, given an out-of distribution (OOD) test set and a pool of …
distribution shift. Specifically, given an out-of distribution (OOD) test set and a pool of …