{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001759213,0.001245264,0.0006994028,0.0004994182,0.0002198196,0.0009348036,0.001310639,0.001027728,0.001107459],"category_scores_gemma":[0.003938012,0.0004277966,0.0007814688,0.000444499,0.00131956,0.001570785,0.001384148,0.002112967,0.0003850967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001204,"about_ca_system_score_gemma":0.0004897159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001246485,"about_ca_topic_score_gemma":0.001496841,"domain_scores_codex":[0.9990672,0.0003981451,0.00003590757,0.0002141467,0.000208091,0.00007659922],"domain_scores_gemma":[0.9983491,0.00094527,0.0002266781,0.0002772107,0.0001434159,0.00005830797],"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":[0.00004414604,0.0000232612,0.0005263666,0.00005911355,0.00004710531,0.00007872601,0.00007155162,0.9051896,0.004176797,0.06127435,0.0005640873,0.02794487],"study_design_scores_gemma":[0.000002707432,0.00003282028,0.0001419789,0.000006861118,0.000005863669,0.00004357369,0.000004284911,0.9825312,0.001438508,0.01521175,0.0005716544,0.000008853041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02253354,0.0005738999,0.9729443,0.0002128517,0.00003546818,0.00003073856,0.00006512675,0.0002358184,0.003368262],"genre_scores_gemma":[0.8330287,0.00112442,0.1556722,0.0003804281,0.0001172842,0.0001508296,0.0003327711,0.0002118851,0.008981479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001759213,"threshold_uncertainty_score":0.009303749,"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."}}