{"id":"W3131298545","doi":"","title":"Differentially Private Generative Models Through Optimal Transport","year":2021,"lang":"en","type":"article","venue":"","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Differential privacy; Computer science; Generative grammar; Generative model; Adversarial system; Artificial intelligence; Synthetic data; Machine learning; Data mining","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":[0.00007668379,0.00018595,0.0002282604,0.00002046875,0.0001625297,0.0001517212,0.0004623127,0.00005986739,0.0002229942],"category_scores_gemma":[0.000007329892,0.0001540106,0.0001366059,0.0002651587,0.00004023514,0.001104544,0.0001574959,0.0001027811,0.00002551098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001906036,"about_ca_system_score_gemma":0.0001034537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002435734,"about_ca_topic_score_gemma":0.0000341927,"domain_scores_codex":[0.9985831,0.00009690921,0.0002319474,0.0005319961,0.0002443523,0.000311643],"domain_scores_gemma":[0.9991977,0.0000336955,0.00004637413,0.0004913282,0.0001514828,0.00007937204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001171985,0.0002336428,0.00006983621,0.000008876484,0.0001788404,0.0001853775,0.002201343,0.2867066,0.0340655,0.6615855,0.001846982,0.01290578],"study_design_scores_gemma":[0.0003691302,0.00004126885,0.0003173869,0.000009636444,0.00001742728,0.00001325508,0.00003690889,0.7609023,0.2161471,0.01805286,0.003767409,0.0003253131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00801465,0.0001477545,0.9767923,0.001259509,0.0003556082,0.00009035497,0.000003640306,0.0001162846,0.0132199],"genre_scores_gemma":[0.5054279,0.00006178931,0.492063,0.0006559113,0.0001202856,0.000008413112,0.000008031095,0.000008181099,0.001646486],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6435326,"threshold_uncertainty_score":0.6280372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02652168241920233,"score_gpt":0.2311368442439867,"score_spread":0.2046151618247844,"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."}}