{"id":"W4285411630","doi":"10.5220/0011307200003283","title":"Resilience of GANs against Adversarial Attacks","year":2022,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Adversarial system; Resilience (materials science); Computer science; Computer security; Artificial intelligence; Physics","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":[0.0005203525,0.0001027844,0.0001564404,0.0001165124,0.0003042576,0.00002530795,0.001641053,0.00002490157,0.0002960778],"category_scores_gemma":[0.0001366763,0.0001048842,0.00007265987,0.0006236077,0.00006252749,0.0003184524,0.001531355,0.0003076357,0.00001507695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007162718,"about_ca_system_score_gemma":0.0001281008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006383082,"about_ca_topic_score_gemma":0.00000434794,"domain_scores_codex":[0.998414,0.0001875005,0.0002489487,0.0003546353,0.0005526688,0.0002422888],"domain_scores_gemma":[0.9990077,0.0001528308,0.0001411903,0.000597771,0.00004458176,0.00005593888],"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":[0.00003304081,0.00009669889,0.004291692,0.00001079809,0.00001891354,0.00004166685,0.001612263,0.8030696,0.002688836,0.1644839,0.002964887,0.02068769],"study_design_scores_gemma":[0.001364544,0.0003192463,0.002964661,0.00001003121,0.00001016477,0.00002466418,0.0008244582,0.9574819,0.00247074,0.002578686,0.03145028,0.0005006373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02481346,0.00002245113,0.9321458,0.0007305006,0.001021357,0.0001229324,0.000002446994,0.0001915963,0.04094945],"genre_scores_gemma":[0.9459027,0.000001919742,0.05255274,0.0003640017,0.00005966501,0.00001036065,0.000002197681,0.000008004834,0.001098423],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9210892,"threshold_uncertainty_score":0.4277052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009104756857500465,"score_gpt":0.2465511924899267,"score_spread":0.2374464356324262,"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."}}