{"id":"W4392236027","doi":"10.1049/qtc2.12088","title":"Successive data injection in conditional quantum GAN applied to time series anomaly detection","year":2024,"lang":"en","type":"article","venue":"IET Quantum Communication","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thales (Canada); Université de Sherbrooke; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Anomaly detection; Series (stratigraphy); Encoding (memory); Qubit; Anomaly (physics); Computer science; Curse of dimensionality; Quantum; State (computer science); Algorithm; Data mining; Artificial intelligence; Physics; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006749826,0.0001681504,0.0001763749,0.0002813935,0.0003021328,0.0005145295,0.001974438,0.0000913764,0.00001125755],"category_scores_gemma":[0.00004978019,0.0001637678,0.00003654425,0.001177115,0.0000535289,0.001400856,0.001077558,0.0003781823,0.0001755012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001042304,"about_ca_system_score_gemma":0.00007296828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002069908,"about_ca_topic_score_gemma":0.0003771644,"domain_scores_codex":[0.9983174,0.0002169089,0.0003824436,0.0005491601,0.0002660354,0.0002680471],"domain_scores_gemma":[0.997761,0.0003363381,0.00009728909,0.00166036,0.00007084112,0.00007423986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002841107,0.0005050816,0.0006636053,0.0003047326,0.0001659428,0.00008634376,0.004831022,0.1582449,0.06411058,0.5916612,0.01401655,0.165126],"study_design_scores_gemma":[0.0001296135,0.0001006874,0.002548213,0.000124476,0.000005488952,0.00003683456,0.00005753051,0.9760006,0.0008474462,0.01592412,0.004006579,0.0002183853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2352858,0.001201612,0.751926,0.007662523,0.0009660897,0.0007701759,0.0000296132,0.0009418287,0.001216299],"genre_scores_gemma":[0.9965971,0.00006168927,0.002716935,0.0001592363,0.0001230464,0.00004208186,0.0002225132,0.0000178489,0.00005950987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8177557,"threshold_uncertainty_score":0.6678258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02295733317364287,"score_gpt":0.2767647711999038,"score_spread":0.2538074380262609,"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."}}