{"id":"W4416249429","doi":"10.1109/ijcnn64981.2025.11229000","title":"Optimization of Graph Neural Networks Training Using Graph Reordering","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Speedup; Graph; Artificial neural network; Training set; Convergence (economics); Dense graph; Attention network; Deep neural networks; Graph bandwidth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004654704,0.001342671,0.0007517722,0.0006235823,0.0003930321,0.0005600855,0.001256953,0.0007272733,0.002594816],"category_scores_gemma":[0.003429146,0.0004294235,0.0005278987,0.0006974865,0.0004734636,0.001239098,0.000672176,0.0008912019,0.0005148788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001057227,"about_ca_system_score_gemma":0.001546729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01321923,"about_ca_topic_score_gemma":0.02920114,"domain_scores_codex":[0.9997054,0.00007797088,0.00001689375,0.00008048607,0.00006598951,0.00005324007],"domain_scores_gemma":[0.9988701,0.0006720067,0.0000911841,0.0001302629,0.0001793818,0.00005705497],"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":[0.00008140834,0.00005722387,0.001270594,0.0000966359,0.00003062821,0.00008750698,0.00004352922,0.9017016,0.003164656,0.002720094,0.003185822,0.08756027],"study_design_scores_gemma":[0.000006549052,0.00001086655,0.00008697206,0.000002369016,0.000002898684,0.000008145688,0.00001135107,0.9976429,0.0007331392,0.001280496,0.0002127501,0.000001462384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1694486,0.0007927999,0.8157744,0.0007535355,0.0001707441,0.0001656531,0.0004479123,0.006504794,0.005941578],"genre_scores_gemma":[0.6187268,0.0002709858,0.3750488,0.0003134354,0.00004373034,0.000219117,0.001323463,0.0005712987,0.00348231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01321923,"threshold_uncertainty_score":0.02628458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03112615784146965,"score_gpt":0.2749506316482858,"score_spread":0.2438244738068162,"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."}}