{"id":"W2979332623","doi":"10.48550/arxiv.1910.04241","title":"Out-of-distribution Detection in Classifiers via Generation","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"MNIST database; Autoencoder; Classifier (UML); Artificial intelligence; Computer science; Inference; Artificial neural network; Machine learning; Pattern recognition (psychology); Detector","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002803711,0.0009601919,0.001106456,0.001093038,0.000539859,0.0009418107,0.001732076,0.001473054,0.001387338],"category_scores_gemma":[0.01207053,0.0006446618,0.0007874956,0.0006324376,0.002098238,0.002441398,0.002191911,0.002186849,0.0005335441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001329997,"about_ca_system_score_gemma":0.000850939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001863425,"about_ca_topic_score_gemma":0.001952157,"domain_scores_codex":[0.9983176,0.000543776,0.00007537995,0.0004694026,0.0004486552,0.0001452227],"domain_scores_gemma":[0.9935805,0.003803278,0.0006795985,0.00118896,0.0006272492,0.0001203675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003158414,0.0001112919,0.006082469,0.0001385713,0.00009514541,0.0002051792,0.0002620994,0.6304005,0.01544059,0.0390332,0.004425981,0.3034892],"study_design_scores_gemma":[0.000008022361,0.00003069396,0.0003225271,0.000008610528,0.000006376986,0.00005413376,0.00001054778,0.9831655,0.004753538,0.01101654,0.0006153536,0.000008195885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02544506,0.0001677213,0.9722464,0.0002321174,0.00002655181,0.00005224651,0.00005517832,0.0009097084,0.0008649708],"genre_scores_gemma":[0.6830594,0.0001893914,0.3135754,0.0003610531,0.000067548,0.000182114,0.0003171194,0.0002381751,0.002009687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002803711,"threshold_uncertainty_score":0.01482761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07386632659431568,"score_gpt":0.2077521175497941,"score_spread":0.1338857909554785,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}