{"id":"W2970731410","doi":"","title":"Exact Combinatorial Optimization with Graph Convolutional Neural Networks","year":2019,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Polytechnique Montréal","funders":"","keywords":"Computer science; Solver; Bipartite graph; Theoretical computer science; Graph; Artificial intelligence; Convolutional neural network; Joins; Deep learning; Branch and bound; Mathematical optimization; Machine learning; Algorithm; Mathematics; Programming language","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":[0.0009933567,0.00122664,0.001094207,0.0006697681,0.0003980419,0.001312679,0.001678661,0.001812478,0.00473389],"category_scores_gemma":[0.005744423,0.0007274356,0.000678269,0.001100893,0.001168204,0.002098575,0.001415919,0.002342929,0.0007789867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002435676,"about_ca_system_score_gemma":0.002310395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01199206,"about_ca_topic_score_gemma":0.02062302,"domain_scores_codex":[0.9995109,0.0001460501,0.00002087163,0.0001239636,0.0001128574,0.00008541542],"domain_scores_gemma":[0.9983786,0.001103911,0.0001324779,0.0001655049,0.0001297831,0.00008970033],"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":[0.00003270902,0.00002596861,0.0002784725,0.00003438563,0.00001309716,0.00002029319,0.00001032102,0.9625239,0.0002092717,0.01598424,0.001572278,0.01929497],"study_design_scores_gemma":[0.000002789214,0.000002025401,0.00001459364,0.000002470089,8.936876e-7,0.000001585105,8.569188e-7,0.9925306,0.00005256259,0.00728116,0.0001094197,9.294946e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03537679,0.0007117163,0.9510381,0.001036148,0.00008981536,0.00006622494,0.0003148112,0.001852222,0.009514086],"genre_scores_gemma":[0.7210596,0.0005420191,0.2661403,0.0005827365,0.0000996114,0.0002717952,0.0008953312,0.0006453791,0.009763231],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01199206,"threshold_uncertainty_score":0.02384454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004437494179705834,"score_gpt":0.2010936910741419,"score_spread":0.1966561968944361,"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."}}