Nicholas Harrison

Multivariate Active Learning and Adaptive Sampling with Multi-Kernel Gaussian Processes

Multivariate Active Learning and Adaptive Sampling With Multi-Kernel Gaussian Processes

In agriculture, understanding the distribution and relationship between different aspects of the environment is important for minimizing chemical use and reducing environmental impact. Traditionally, it is done by manually collecting samples on the field and then sending them to a laboratory for ana

Automated Testing of Spatially-Dependent Environmental Hypotheses through Active Transfer Learning

The efficient collection of samples is an important factor in outdoor information gathering applications on account of high sampling costs such as time, energy, and potential destruction to the environment. Utilization of available a-priori data can be a powerful tool for increasing efficiency. Howe…