{"id":"W2970641149","doi":"","title":"Residual Flows for Invertible Generative Modeling","year":2019,"lang":"en","type":"article","venue":"Neural Information Processing Systems","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Invertible matrix; Residual; Lipschitz continuity; Discriminative model; Transformation (genetics); Computer science; Mathematics; Algorithm; Generative model; Artificial neural network; Density estimation; Applied mathematics; Mathematical optimization; Generative grammar; Artificial intelligence; Statistics; Estimator; Pure mathematics","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":[0.000319449,0.0001486222,0.000192298,0.0001149159,0.0002532199,0.0009929836,0.0003669242,0.00006753514,0.0000032004],"category_scores_gemma":[0.000044415,0.0001239094,0.00004989617,0.0002458624,0.000009116437,0.006098606,0.00006901435,0.00008360596,0.00006522751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004450973,"about_ca_system_score_gemma":0.00009587304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003064854,"about_ca_topic_score_gemma":0.000002134697,"domain_scores_codex":[0.9987963,0.00005100983,0.0004475906,0.0001918747,0.0002547091,0.0002585509],"domain_scores_gemma":[0.9990717,0.00003972145,0.0001995032,0.000234458,0.0003960702,0.00005858601],"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":[0.00001061425,0.000005576745,0.00002543953,0.0001384983,0.000008135023,1.246845e-7,0.001233025,0.9744765,0.001070937,0.002030375,0.00118018,0.01982064],"study_design_scores_gemma":[0.0003173068,0.0000569346,0.000004262528,0.00005114075,0.000003812327,0.000005275453,0.0002143301,0.9946348,0.001216102,0.0001405675,0.003190853,0.0001645974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01485177,0.0001675184,0.9817134,0.0004099669,0.001029753,0.0005957883,0.000004988368,0.0001451172,0.001081743],"genre_scores_gemma":[0.9733449,0.000002817032,0.02551266,0.0005150319,0.0002440192,0.00008050368,0.00002165848,0.000007781265,0.0002706502],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9584931,"threshold_uncertainty_score":0.9575363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02398896971344965,"score_gpt":0.2394272595567821,"score_spread":0.2154382898433325,"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."}}