Nature

Exact Gaussian processes for massive datasets via non-stationary sparsity-discovering kernels

A Gaussian Process (GP) is a prominent mathematical framework for stochastic function approximation in science and engineering applications. Its success is largely attributed to the GP’s analytical ...
Nature

Gaussian process regression with physics-guided pseudo-sample augmentation for wear prediction under sparse measurements in milling

Tool wear prediction is essential to ensure machining quality and sustainability. Hybrid physics-data Gaussian process regression (GPR) methods integrate domain knowledge with data-driven learning, ...
DLR

Video: Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes

This video presents an uncertainty estimation algorithm for planetary exploration aerial robots - ARDEA. The robot detects rovers and landers semantically. The key technology behind is a sparse ...