{"id":"W2768910279","doi":"10.48550/arxiv.1711.06020","title":"Global versus Localized Generative Adversarial Nets","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research","keywords":"Manifold (fluid mechanics); Tangent space; Subspace topology; Generator (circuit theory); Mathematics; Manifold alignment; Classifier (UML); Topology (electrical circuits); Tangent; Computer science; Locality; Orthonormality; Artificial intelligence; Algorithm; Nonlinear dimensionality reduction; Geometry; Orthonormal basis; Combinatorics; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003045121,0.0006300102,0.0006742806,0.0001226401,0.0006836181,0.0006329706,0.00382442,0.000534108,0.00007541051],"category_scores_gemma":[0.0001562619,0.0006991036,0.0004942809,0.000353499,0.0003262446,0.0008497979,0.004038371,0.0004980107,0.0001561753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005307124,"about_ca_system_score_gemma":0.0006102504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007470067,"about_ca_topic_score_gemma":0.0004150353,"domain_scores_codex":[0.9965616,0.0004075352,0.0002882329,0.001877613,0.0001982168,0.0006667834],"domain_scores_gemma":[0.9961486,0.0001327862,0.0005543201,0.002496824,0.0003250539,0.000342445],"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":[0.0004254507,0.0001050513,0.000365968,0.00001818655,0.0004942674,0.0006110735,0.0001323657,0.8950157,0.00001490295,0.09187455,0.00689933,0.004043176],"study_design_scores_gemma":[0.002876711,0.0001333023,0.0003590308,0.00006050138,0.0001774067,0.000003233852,0.0000338138,0.9569345,0.0001576905,0.02960757,0.008764252,0.0008919824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005957513,0.0001662154,0.9717439,0.0003838463,0.006975553,0.0004166443,0.00007553447,0.0002511671,0.01402963],"genre_scores_gemma":[0.9859331,0.0002149348,0.01173538,0.0001488152,0.0007384758,0.000002266712,0.00003791581,0.00002213093,0.001166949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9799756,"threshold_uncertainty_score":0.999546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08737791151025937,"score_gpt":0.2194203505936257,"score_spread":0.1320424390833663,"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."}}