{"id":"W4416932885","doi":"10.48550/arxiv.2512.00170","title":"We Still Don't Understand High-Dimensional Bayesian Optimization","year":2025,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Research England; Natural Sciences and Engineering Research Council of Canada; National Science Foundation; Government of Canada; Canadian Institute for Advanced Research","keywords":"Curse of dimensionality; Bayesian optimization; Bayesian probability; Exploit; Gaussian process; Locality; Computation; Optimization problem","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000414878,0.001116684,0.0009907983,0.0008902421,0.0007385879,0.0007166472,0.003634889,0.0009713589,0.001091052],"category_scores_gemma":[0.00006940929,0.001315704,0.000458304,0.002839298,0.0005170047,0.001340027,0.003741245,0.001331263,0.0001204734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008279889,"about_ca_system_score_gemma":0.00232354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003671683,"about_ca_topic_score_gemma":0.0001046837,"domain_scores_codex":[0.9938623,0.0003744198,0.0007817427,0.003464342,0.0003918614,0.001125337],"domain_scores_gemma":[0.9952016,0.0002992852,0.0008520817,0.002288511,0.0007262321,0.0006323222],"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":[0.0000958291,0.0002063628,0.0001921472,0.0003563728,0.0001675277,0.0003089048,0.0003979203,0.6806266,0.000004688799,0.3160846,0.0003989929,0.001160068],"study_design_scores_gemma":[0.001246952,0.0001592857,0.0001397143,0.001057554,0.0002739635,0.00001549203,0.0002508188,0.893836,0.0001029258,0.1013316,0.0003836116,0.001202081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003360583,0.0002847949,0.9863724,0.001590805,0.002179786,0.0006960818,0.0001378221,0.0003074562,0.005070232],"genre_scores_gemma":[0.9575896,0.001946042,0.02754594,0.0003590805,0.0001178911,0.000001631664,0.00006355126,0.00003539689,0.0123409],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9588265,"threshold_uncertainty_score":0.9998221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0456381393242947,"score_gpt":0.1854230976882942,"score_spread":0.1397849583639995,"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."}}