{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001081713,0.0007672302,0.000768766,0.0008154946,0.0004521281,0.001348552,0.001496723,0.001585622,0.002346389],"category_scores_gemma":[0.008074516,0.0004454933,0.0005324066,0.0008435695,0.001974137,0.003668427,0.003287372,0.002495265,0.0004889526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009964007,"about_ca_system_score_gemma":0.0006223744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007343835,"about_ca_topic_score_gemma":0.0009299656,"domain_scores_codex":[0.9992643,0.0002241455,0.00003267317,0.000179993,0.0002252484,0.00007364831],"domain_scores_gemma":[0.9971696,0.001243583,0.0005460771,0.0006720487,0.0002007642,0.0001679226],"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":[0.00008412864,0.00006032424,0.0009331835,0.0001152816,0.00005349745,0.0001235769,0.0001707173,0.3004599,0.009996509,0.6320867,0.001879738,0.0540364],"study_design_scores_gemma":[0.00000690094,0.00003950961,0.00021272,0.000009999451,0.000005161807,0.00003599128,0.00000913989,0.8319463,0.001436743,0.1652369,0.001049408,0.00001129795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0224633,0.0001787288,0.9738547,0.0003335915,0.00004290449,0.00001572257,0.00003366937,0.0001581424,0.002919243],"genre_scores_gemma":[0.7858134,0.0003879725,0.2044023,0.0003648321,0.0002581994,0.0001498438,0.0001868184,0.0003310581,0.008105666],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002346389,"threshold_uncertainty_score":0.007849455,"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."}}