{"id":"W2962863897","doi":"10.1007/s00365-019-09467-0","title":"Compressive Hermite Interpolation: Sparse, High-Dimensional Approximation from Gradient-Augmented Measurements","year":2019,"lang":"en","type":"article","venue":"Constructive Approximation","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Hermite interpolation; Tensor product; Applied mathematics; Sobolev space; Interpolation (computer graphics); Curse of dimensionality; Norm (philosophy); Chebyshev polynomials; Mathematical analysis; Hermite polynomials; Pure mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001025607,0.0002969738,0.0003193929,0.0001882441,0.0000877771,0.00007770679,0.0001696846,0.0001405342,0.000246169],"category_scores_gemma":[0.00002083416,0.0003120968,0.00007832215,0.0002262008,0.00008695319,0.00055276,0.00006282593,0.0002120735,0.0001588816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001710157,"about_ca_system_score_gemma":0.00002047131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004940603,"about_ca_topic_score_gemma":0.000005276919,"domain_scores_codex":[0.9984496,0.00008720691,0.0004067947,0.0003874092,0.0004144668,0.000254478],"domain_scores_gemma":[0.9990341,0.00006311376,0.0001850911,0.0003862254,0.0002587347,0.00007275351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002938018,0.0002145844,0.02172653,0.000136744,0.0009888546,0.000009889413,0.001443155,0.032027,0.8701826,0.01390734,0.003482874,0.05558666],"study_design_scores_gemma":[0.001671743,0.00006216197,0.017717,0.0003964296,0.00007760725,0.00001815714,0.0002173004,0.6954262,0.2701292,0.01348991,0.0001812646,0.0006130598],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.907483,0.0001614815,0.08412262,0.00002403471,0.00102492,0.0008458282,0.00005008392,0.0007522535,0.00553572],"genre_scores_gemma":[0.9706965,0.000004341116,0.02856879,0.0000502693,0.0001037943,0.00005086532,0.0004562291,0.00004332904,0.00002585792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6633992,"threshold_uncertainty_score":0.9999331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01923653185925205,"score_gpt":0.2159038391327625,"score_spread":0.1966673072735104,"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."}}