{"id":"W3116383660","doi":"10.1162/neco_a_01416","title":"Least kth-Order and Rényi Generative Adversarial Networks","year":2021,"lang":"en","type":"article","venue":"Neural Computation","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Generator (circuit theory); MNIST database; Parameterized complexity; Discriminator; Function (biology); Measure (data warehouse); Minimax; Distortion (music)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001116739,0.0001665048,0.0001809612,0.0000446303,0.0002603045,0.0003314996,0.0001593644,0.00006694158,0.00001721414],"category_scores_gemma":[0.00006248905,0.0001609603,0.00005285603,0.0004289441,0.00004944646,0.0006134756,0.0002079363,0.0001503094,0.000009023595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002504699,"about_ca_system_score_gemma":0.00005929681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001878101,"about_ca_topic_score_gemma":0.00002582178,"domain_scores_codex":[0.9986369,0.0002487144,0.0002056623,0.0004804285,0.0001874011,0.0002408903],"domain_scores_gemma":[0.999214,0.000147067,0.00008503172,0.0001825047,0.0002779496,0.00009346951],"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":[0.00001727229,0.00003931731,0.0002635487,0.000004917119,0.00003596271,0.00005029139,0.0004041003,0.8488303,0.002134775,0.003222541,0.001977554,0.1430194],"study_design_scores_gemma":[0.0004941599,0.00005543256,0.002672922,0.00000683955,0.00001159454,0.00003178461,0.00003336958,0.9937716,0.001288334,0.0008510781,0.0006035335,0.0001794133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01416078,0.0003875008,0.9816694,0.001905566,0.001123839,0.0001121221,0.000001530679,0.00008467779,0.0005546025],"genre_scores_gemma":[0.9153717,0.00002895649,0.08291931,0.0009478926,0.0005643227,0.000005932196,0.00002383036,0.00001018773,0.0001279127],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9012108,"threshold_uncertainty_score":0.656377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336777913503517,"score_gpt":0.2325247675236398,"score_spread":0.2191569883886047,"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."}}