{"id":"W3158469333","doi":"","title":"Implicit Regularization via Neural Feature Alignment","year":2021,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence and Statistics","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Université de Montréal","funders":"","keywords":"Regularization (linguistics); Tangent; Heuristic; Computer science; Artificial intelligence; Algorithm; Feature selection; Kernel (algebra); Artificial neural network; Mathematics; Pattern recognition (psychology); Discrete mathematics; Geometry","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":[0.00005754452,0.000139123,0.0001140898,0.00007778266,0.00005846807,0.000110998,0.000112817,0.00008355394,0.0004753188],"category_scores_gemma":[0.00009300536,0.0001560665,0.00001881221,0.000100639,0.00006017408,0.00008857384,0.00002978057,0.0001562287,0.00003709688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004837088,"about_ca_system_score_gemma":0.0000187997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002916991,"about_ca_topic_score_gemma":0.00001912594,"domain_scores_codex":[0.9992123,0.00002175333,0.0002303463,0.0001948726,0.0001852528,0.0001554618],"domain_scores_gemma":[0.9994922,0.00008126372,0.00003052186,0.000123529,0.0002078482,0.00006458873],"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":[0.00001116871,0.00002208584,0.00003224783,0.00001100395,0.00003773685,0.00003189988,0.0001718805,0.2179978,0.006655878,0.7133565,0.0005324823,0.06113932],"study_design_scores_gemma":[0.00002328826,0.00002547003,0.0001311832,0.00001731499,0.000008377754,0.00003412127,0.0001753701,0.9285051,0.01359152,0.05682835,0.0005004447,0.000159419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001009176,0.00004404793,0.9915028,0.0009643854,0.001163748,0.00006224876,0.0001251422,0.0001100863,0.005018411],"genre_scores_gemma":[0.9632009,0.0002636162,0.0354249,0.000179351,0.0001367112,0.00001337732,0.0002133187,0.00002278464,0.0005449808],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9621918,"threshold_uncertainty_score":0.6364206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03631847140534972,"score_gpt":0.2869032862195527,"score_spread":0.250584814814203,"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."}}