{"id":"W2963782635","doi":"10.17863/cam.40744","title":"Deep Graph Infomax","year":2018,"lang":"en","type":"article","venue":"Apollo (University of Cambridge)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":332,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"European Commission","keywords":"Infomax; Computer science; Graph; Artificial intelligence; Unsupervised learning; Node (physics); Machine learning; Competitive learning; Feature learning; Theoretical computer science","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":[0.0007064763,0.001657323,0.001180649,0.00111413,0.0004822497,0.001421859,0.003027491,0.001676335,0.008604811],"category_scores_gemma":[0.002976981,0.0005071691,0.001167015,0.001427745,0.0008099319,0.003280035,0.00182457,0.002499832,0.003486204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001455545,"about_ca_system_score_gemma":0.001191526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004653758,"about_ca_topic_score_gemma":0.01005588,"domain_scores_codex":[0.9995172,0.0000839478,0.0000165856,0.0001937463,0.0001214992,0.00006699518],"domain_scores_gemma":[0.9992899,0.0002791369,0.00007124751,0.0001979075,0.0001053793,0.00005643279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003379139,0.0002754389,0.001815193,0.0003982007,0.0002502849,0.0001557888,0.00009931369,0.4205966,0.009864644,0.0619624,0.05734413,0.4469002],"study_design_scores_gemma":[0.00001298242,0.00003827304,0.0002427375,0.00001805039,0.00002442803,0.00003398016,0.0000101504,0.943495,0.004179309,0.04655071,0.005381108,0.00001337456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02166747,0.001416856,0.9443838,0.001363168,0.0002626194,0.0001150874,0.004373952,0.01492799,0.01148908],"genre_scores_gemma":[0.5221313,0.001357781,0.4312994,0.001641549,0.0002798479,0.000351349,0.01954577,0.001623489,0.02176966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008604811,"threshold_uncertainty_score":0.028786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007093247053127333,"score_gpt":0.1900923582138747,"score_spread":0.1829991111607473,"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."}}