{"id":"W4360604838","doi":"10.1109/icnc57223.2023.10074146","title":"Evaluating Generative Adversarial Networks: A Topological Approach","year":2023,"lang":"en","type":"article","venue":"","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Persistent homology; Metric (unit); Computer science; Topology (electrical circuits); Topological data analysis; Convolution (computer science); Manifold (fluid mechanics); Generative grammar; Algebraic number; Algebraic topology; Artificial neural network; Adversarial system; Artificial intelligence; Theoretical computer science; Mathematics; Algorithm; Pure mathematics; Homotopy; Combinatorics","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":[0.007619779,0.001735843,0.001461236,0.002310768,0.0005424437,0.001948897,0.002289494,0.002337443,0.002285946],"category_scores_gemma":[0.02490974,0.0006185383,0.0009156762,0.001031462,0.002496762,0.003429539,0.003261169,0.002521664,0.0003742977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00191486,"about_ca_system_score_gemma":0.0009624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00166617,"about_ca_topic_score_gemma":0.001806056,"domain_scores_codex":[0.9972014,0.001480998,0.0001159548,0.000381956,0.0006823042,0.0001373082],"domain_scores_gemma":[0.9841909,0.01214446,0.0009200358,0.001180491,0.001101535,0.0004624385],"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":[0.00005956638,0.00002730072,0.001185747,0.00005174269,0.00006250307,0.00004240574,0.00001921361,0.9601448,0.0005158045,0.01759956,0.0006004739,0.01969092],"study_design_scores_gemma":[0.000003145047,0.00002764863,0.00007721153,0.000006182618,0.000004527365,0.00001177956,0.000003970309,0.9892757,0.0003205626,0.01014519,0.0001196676,0.000004467614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04001849,0.0006398239,0.9550326,0.0009172409,0.00008307719,0.00006697542,0.0002161313,0.0008067872,0.002218971],"genre_scores_gemma":[0.8561802,0.0005666054,0.1394418,0.0004384698,0.0001831082,0.0001797293,0.0009065113,0.0002966554,0.001806808],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007619779,"threshold_uncertainty_score":0.04029775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1127029968944292,"score_gpt":0.3515251318734108,"score_spread":0.2388221349789817,"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."}}