{"id":"W3187633063","doi":"10.24963/ijcai.2021/452","title":"Unsupervised Path Representation Learning with Curriculum Negative Sampling","year":2021,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; Canadian Institute for Advanced Research; HEC Montréal","funders":"Innovationsfonden; Villum Fonden","keywords":"Computer science; Path (computing); Artificial intelligence; Machine learning; Representation (politics); ENCODE; Unsupervised learning; Feature learning; Ranking (information retrieval)","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":[0.0008672647,0.0012308,0.00105843,0.001083767,0.00057203,0.0005961432,0.002080732,0.0011843,0.002230211],"category_scores_gemma":[0.004298184,0.0005314256,0.0009961434,0.001289548,0.0009980629,0.001992039,0.001295945,0.002161328,0.0006650007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009141201,"about_ca_system_score_gemma":0.001279149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005760157,"about_ca_topic_score_gemma":0.01058684,"domain_scores_codex":[0.9994281,0.0001739528,0.00002079121,0.0002171266,0.00009229244,0.00006759843],"domain_scores_gemma":[0.9982962,0.0009431916,0.0001475615,0.0002674566,0.0002769754,0.00006864742],"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":[0.0002705374,0.000339303,0.004691781,0.000182399,0.0001035258,0.0001206243,0.0001474964,0.6166565,0.006405429,0.01498499,0.007285056,0.3488123],"study_design_scores_gemma":[0.00001379188,0.00004039451,0.0003116712,0.000006326892,0.000007006056,0.0000167718,0.00001193146,0.9907078,0.001085007,0.007310665,0.0004818449,0.000006750599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04629425,0.0001996281,0.9499404,0.0001665255,0.00004000242,0.0001120842,0.0003520252,0.001669055,0.001226071],"genre_scores_gemma":[0.6833891,0.0002354197,0.3065676,0.0003135176,0.00009517577,0.0005208023,0.003665787,0.0002675872,0.004945086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005760157,"threshold_uncertainty_score":0.01145327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0124466022333569,"score_gpt":0.2313686672399588,"score_spread":0.2189220650066019,"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."}}