{"id":"W4382317874","doi":"10.1609/aaai.v37i8.26102","title":"GENNAPE: Towards Generalized Neural Architecture Performance Estimators","year":2023,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada); University of Alberta","funders":"","keywords":"Computer science; Artificial neural network; Artificial intelligence; Architecture; Network architecture; Estimator; Graph; Machine learning; Time delay neural network; Theoretical computer science; 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":[0.002140423,0.001494346,0.0008268456,0.001038259,0.0002584272,0.0008953072,0.002060702,0.001055845,0.001492687],"category_scores_gemma":[0.008669328,0.0005068055,0.0004850918,0.0005777216,0.0007215298,0.001590773,0.001334628,0.001929493,0.0005841717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009381567,"about_ca_system_score_gemma":0.001210173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004054816,"about_ca_topic_score_gemma":0.00730727,"domain_scores_codex":[0.9992168,0.00022521,0.00003629471,0.0002389496,0.0002046333,0.00007809086],"domain_scores_gemma":[0.9975419,0.001249589,0.0002677032,0.0003765225,0.0004918817,0.00007245508],"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":[0.0001134268,0.00006524243,0.004590425,0.0001240186,0.0001221306,0.00004730775,0.00005710138,0.8228774,0.004445152,0.005296469,0.00282918,0.1594321],"study_design_scores_gemma":[0.00000523982,0.00003153712,0.0003426781,0.000009482824,0.000008059174,0.00001216415,0.000006668635,0.9945554,0.00139632,0.003281697,0.0003454529,0.000005294113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05067701,0.0007673185,0.9420155,0.0002090903,0.00005050089,0.00006603073,0.0003041866,0.004307271,0.001602976],"genre_scores_gemma":[0.7101797,0.0003544919,0.2842025,0.00027994,0.00005291587,0.0002566116,0.001534878,0.0006747249,0.002464265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004054816,"threshold_uncertainty_score":0.01131976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06564785021917369,"score_gpt":0.2948797587371016,"score_spread":0.229231908517928,"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."}}