Out-of-distribution detection with deep nearest neighbors

Y Sun, Y Ming, X Zhu, Y Li - International Conference on …, 2022 - proceedings.mlr.press
Abstract Out-of-distribution (OOD) detection is a critical task for deploying machine learning
models in the open world. Distance-based methods have demonstrated promise, where …
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Out-of-Distribution Detection with Deep Nearest Neighbors

Y Sun, Y Ming, X Zhu, Y Li - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Abstract Out-of-distribution (OOD) detection is a critical task for deploying machine learning
models in the open world. Distance-based methods have demonstrated promise, where …

Out-of-Distribution Detection with Deep Nearest Neighbors

Y Sun, Y Ming, X Zhu, Y Li - International Conference on …, 2022 - proceedings.mlr.press
Abstract Out-of-distribution (OOD) detection is a critical task for deploying machine learning
models in the open world. Distance-based methods have demonstrated promise, where …

Out-of-Distribution Detection with Deep Nearest Neighbors

Y Sun, Y Ming, X Zhu, Y Li - arXiv preprint arXiv:2204.06507, 2022 - arxiv.org
Out-of-distribution (OOD) detection is a critical task for deploying machine learning models
in the open world. Distance-based methods have demonstrated promise, where testing …