{"id":"W4385764544","doi":"10.24963/ijcai.2023/101","title":"GeNAS: Neural Architecture Search with Better Generalization","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Architecture; Generalization; Artificial neural network; Artificial intelligence; Network architecture; Segmentation; Measure (data warehouse); Flatness (cosmology); Pattern recognition (psychology); Machine learning; Data mining; Mathematics","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":[0.003061533,0.002262118,0.001429049,0.002355818,0.0005975873,0.001327996,0.002044261,0.002231123,0.004540578],"category_scores_gemma":[0.007941551,0.0005331836,0.001292543,0.001069103,0.001129033,0.00227447,0.001740661,0.002151269,0.001079014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128538,"about_ca_system_score_gemma":0.002069971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003855801,"about_ca_topic_score_gemma":0.008608736,"domain_scores_codex":[0.998717,0.000426069,0.0000915253,0.0003248374,0.0003154428,0.000125064],"domain_scores_gemma":[0.9976997,0.0009267961,0.0002850694,0.0005457563,0.0004193923,0.0001233765],"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":[0.0004943297,0.0003116726,0.007573292,0.0002465491,0.0003792007,0.0002127345,0.0001158153,0.5920668,0.008355518,0.01222631,0.01251945,0.3654982],"study_design_scores_gemma":[0.00004676204,0.0001740713,0.0005858752,0.00001937311,0.00003189727,0.0000548522,0.00002093141,0.9895514,0.001954232,0.006631806,0.0009170042,0.00001181562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.194198,0.00258281,0.7842066,0.00131505,0.0002532241,0.0003491413,0.0007784143,0.008862986,0.007453753],"genre_scores_gemma":[0.7181177,0.0004353915,0.2706544,0.0007603442,0.0001475367,0.0003545232,0.001851428,0.0006505858,0.007028116],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004540578,"threshold_uncertainty_score":0.01619112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0207507601510287,"score_gpt":0.2667131147926719,"score_spread":0.2459623546416432,"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."}}