{"id":"W2947994715","doi":"10.48550/arxiv.1905.12797","title":"Bandlimiting Neural Networks Against Adversarial Attacks","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Adversarial system; Computer security; Computer science; Artificial neural network; Deep neural networks; Artificial intelligence","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":[0.001857707,0.001069432,0.0009435613,0.0006803277,0.0003926539,0.0007617815,0.0009742164,0.001318257,0.001760095],"category_scores_gemma":[0.008020779,0.0003583423,0.0004761474,0.000318773,0.001970394,0.00180831,0.002299382,0.001983552,0.0004737782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007206718,"about_ca_system_score_gemma":0.0004480652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006229728,"about_ca_topic_score_gemma":0.0005420594,"domain_scores_codex":[0.9990603,0.0002631578,0.00004152661,0.0001756295,0.0003095429,0.0001497753],"domain_scores_gemma":[0.9971645,0.001812206,0.0002526756,0.0005127397,0.0001821293,0.00007571787],"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":[0.0002120878,0.00004898854,0.0007083003,0.0001031215,0.00007445863,0.0001920274,0.00008594428,0.8485298,0.02384441,0.04651061,0.001550276,0.07813992],"study_design_scores_gemma":[0.000004448389,0.00003378556,0.0001139594,0.000008817164,0.000005352141,0.00004708139,0.000008794968,0.9805797,0.004954373,0.01381807,0.0004194868,0.000006120596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06072768,0.0004868328,0.9338112,0.000431513,0.00007620991,0.00003434673,0.00004377126,0.0008210342,0.003567405],"genre_scores_gemma":[0.9277029,0.0002956517,0.06875157,0.0002166254,0.00005884697,0.00006249941,0.00006823836,0.0001010238,0.002742705],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001857707,"threshold_uncertainty_score":0.009824634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04896313561997109,"score_gpt":0.1981638420360703,"score_spread":0.1492007064160992,"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."}}