{"id":"W3102100346","doi":"10.1016/j.inffus.2021.05.008","title":"A review of uncertainty quantification in deep learning: Techniques, applications and challenges","year":2021,"lang":"en","type":"review","venue":"Information Fusion","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":2453,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; University of Waterloo","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Variety (cybernetics); Artificial intelligence; Field (mathematics); Deep learning; Machine learning; Reinforcement learning; Uncertainty quantification; Data science; Image processing; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04813692263496225,"score_gpt":0.3210454838638859,"score_spread":0.2729085612289237,"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."}}