{"id":"W4403885263","doi":"10.1145/3680528.3687682","title":"Robust Symmetry Detection via Riemannian Langevin Dynamics","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Army Research Laboratory; Azrieli Foundation","keywords":"Homogeneous space; Robustness (evolution); Computer science; Symmetrization; Rotational symmetry; Symmetry (geometry); Noise (video); Artificial intelligence; Statistical physics; Mathematics; Physics; Geometry; Image (mathematics); Mathematical analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001352243,0.0008256056,0.001037502,0.0008354763,0.0004930318,0.001057244,0.00138562,0.001233606,0.001932229],"category_scores_gemma":[0.004635857,0.000594389,0.000892383,0.000394247,0.001715696,0.001249682,0.00199628,0.001701219,0.0005970923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009627531,"about_ca_system_score_gemma":0.0007963182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00177501,"about_ca_topic_score_gemma":0.001610419,"domain_scores_codex":[0.9992701,0.0002335871,0.0000251863,0.0001742174,0.0002299539,0.00006706722],"domain_scores_gemma":[0.9984235,0.0007957612,0.0002737422,0.0002469314,0.0001456516,0.0001144838],"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":[0.0001599342,0.00004354706,0.001716531,0.00008186547,0.00006456944,0.0002667779,0.0001139393,0.8090471,0.01729516,0.09690475,0.002438579,0.07186727],"study_design_scores_gemma":[0.000003708699,0.000006975856,0.00007359254,0.000002682367,0.000001441368,0.0000246105,0.000003852396,0.9859424,0.0008603958,0.01286639,0.0002073164,0.000006571297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02775913,0.000101983,0.969371,0.0003026204,0.00004168233,0.00003102219,0.00006392288,0.0004735679,0.001855021],"genre_scores_gemma":[0.7873963,0.0001878278,0.2062202,0.0002388095,0.0000607868,0.00009270223,0.0002620342,0.0003543333,0.005186843],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001932229,"threshold_uncertainty_score":0.007151365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01822300559786394,"score_gpt":0.2216740166643421,"score_spread":0.2034510110664781,"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."}}