VIF approximations combine inducing points and Vecchia methods with an efficient neighbor search to deliver computationally efficient, accurate, and stable Gaussian process inference on large data.
Scalable log determinants for G aussian process kernel learning
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Vecchia-Inducing-Points Full-Scale Approximations for Gaussian Processes
VIF approximations combine inducing points and Vecchia methods with an efficient neighbor search to deliver computationally efficient, accurate, and stable Gaussian process inference on large data.