A Bayesian Framework for Built-in Input Dimension Reduction for Gaussian Process Modeling

arXiv 2607.19498•c074ff47524ccf4e3fcf9d5393186f4ff5bf55804d1c2c9ee5088b10a29347e8
DKMDLoRARELTA-SGLDStatLoRAannealingappend-only-attacksbayesiancausal-inferencecovariate-shiftdata-poisoningdeep-gaussian-processdistribution-shiftflowsgaussian-processhamiltonian-monte-carlolow-rank-adaptationmachine-learningmodel-fine-tuningmolecular-designpoisoning-auditsde-trainingsghmc-sgldstiefel-manifoldtotal-influencetraining-stability

Paper metadata

arXiv ID
2607.19498
Version
Not specified by this published record
Category
Statistics — Machine Learning (stat.ML)

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Evidence and limitations

Source ID
arxiv_stat_ml
Record identifier
c074ff47524ccf4e3fcf9d5393186f4ff5bf55804d1c2c9ee5088b10a29347e8
Enrichment time
2026-07-23T07:24:04Z
AI-assisted enrichment
Yes

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A Bayesian Framework for Built-in Input Dimension Reduction for Gaussian Process Modeling · Baitaphish