{"id":"W3158338018","doi":"","title":"Detection and Defense of Topological Adversarial Attacks on Graphs","year":2021,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence and Statistics","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Adversarial system; Computer science; Computer security; Topology (electrical circuits); Mathematics; Artificial intelligence; 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":[0.001230571,0.0007465901,0.0006754086,0.001172819,0.000455556,0.00107041,0.001030308,0.001350626,0.001059054],"category_scores_gemma":[0.008650489,0.0003145687,0.0005294668,0.0005812415,0.001144879,0.00164744,0.00224603,0.00133789,0.0002591859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000709569,"about_ca_system_score_gemma":0.0004659515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006134818,"about_ca_topic_score_gemma":0.0005962285,"domain_scores_codex":[0.9988216,0.0004082619,0.00003392072,0.000175767,0.0003672789,0.000193139],"domain_scores_gemma":[0.9953571,0.002600705,0.0006016686,0.0008290983,0.0003863804,0.0002250764],"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":[0.0006261679,0.0001423468,0.003981572,0.0001134163,0.0001327431,0.0003096665,0.0001598853,0.7725815,0.02633987,0.1053647,0.00567133,0.08457682],"study_design_scores_gemma":[0.000006855747,0.00004585685,0.0003540067,0.000004845303,0.000007202708,0.00007587524,0.00001988665,0.9819334,0.002483428,0.01470623,0.0003578282,0.000004544373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3615445,0.000494878,0.6256797,0.001574968,0.0001704871,0.0001379193,0.000252479,0.001333677,0.008811262],"genre_scores_gemma":[0.98272,0.0001260478,0.01575113,0.00009411572,0.00003679651,0.00002296911,0.0001277176,0.00002453114,0.001096622],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001350626,"threshold_uncertainty_score":0.006507933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09422810246771066,"score_gpt":0.339257572962414,"score_spread":0.2450294704947034,"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."}}