Adaptive multi-resolution Gaussian processes: Scalable exact inference with naturally data-sparse covariance matrices
arXiv:2609.30348v1 Announce Type: new Abstract: Gaussian processes constitute a cornerstone of probabilistic machine learning, yet scaling them to large datasets typically forces a trade-off between computational efficiency and model fidelity. This work bridges this gap by presenting an adaptive mu…
Read the full story at arXiv stat.ML ↗
Timeline · 1 report
- 2026-09-28 04:00 · arXiv stat.ML
Adaptive multi-resolution Gaussian processes: Scalable exact inference with naturally data-sparse covariance matrices