Environmental sensor placement with convolutional Gaussian neural processes

Environmental sensor placement with convolutional Gaussian neural processes

Environmental sensors are crucial for monitoring weather conditions and the impacts of climate change. However, it is challenging to place sensors in a way that maximises the informativeness of their measurements, particularly in remote regions like Antarctica. Probabilistic machine learning models...

Full description

Bibliographic Details
Main Authors: Tom R. Andersson, Wessel P. Bruinsma, Stratis Markou, James Requeima, Alejandro Coca-Castro, Anna Vaughan, Anna-Louise Ellis, Matthew A. Lazzara, Dani Jones, Scott Hosking, Richard E. Turner
Format: Article
Language:English
Published: Cambridge University Press 2023-01-01
Series:Environmental Data Science
Subjects:
active learning
meta-learning
neural processes
sensor placement
Online Access:https://www.cambridge.org/core/product/identifier/S2634460223000225/type/journal_article

Internet

https://www.cambridge.org/core/product/identifier/S2634460223000225/type/journal_article

Similar Items