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, ...
Nature

Biological direct-shortcut deep residual learning for sparse visual processing

We show, based on the following three grounds, that the primary visual cortex (V1) is a biological direct-shortcut deep residual learning neural network (ResNet) for sparse visual processing: (1) We ...
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 ...