%0 Conference Paper %1 lucells %A Lu, Alex %A Lu, Amy %A Schormann, Wiebke %A Ghassemi, Marzyeh %A Andrews, David %A Moses, Alan %D 2019 %K anomaly-detection benchmarks neurips2019 outliers %P 1852-1860 %T The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers %U https://papers.nips.cc/paper/8461-the-cells-out-of-sample-coos-dataset-and-benchmarks-for-measuring-out-of-sample-generalization-of-image-classifiers

@inproceedings{lucells, added-at = {2020-01-15T17:39:35.000+0100}, author = {Lu, Alex and Lu, Amy and Schormann, Wiebke and Ghassemi, Marzyeh and Andrews, David and Moses, Alan}, biburl = {https://www.bibsonomy.org/bibtex/29b6f3993934fefd1ccf62d03cbd6da89/kirk86}, description = {The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers}, interhash = {3a5addc81d0cf6762566eb9d1cdf865a}, intrahash = {9b6f3993934fefd1ccf62d03cbd6da89}, keywords = {anomaly-detection benchmarks neurips2019 outliers}, pages = {1852-1860}, timestamp = {2020-01-15T17:39:35.000+0100}, title = {The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers}, type = {misc}, url = {https://papers.nips.cc/paper/8461-the-cells-out-of-sample-coos-dataset-and-benchmarks-for-measuring-out-of-sample-generalization-of-image-classifiers}, year = 2019 }