59 citations · 66 across the 7 of their papers we have counts for
8 papers
Data-driven Optimal Sensor Placement for Aerosol Monitoring in the UK
Talha Ansar, Waqar Muhammad Ashraf, Alejandro Coca-Castro +3
We develop a data-driven sensor-placement framework and apply it to aerosol monitoring in the United Kingdom (UK). A trained convolutional Gaussian neural process is embedded withi…
Technical overview and architecture of the FastNet Machine Learning weather prediction model, version 1.0
Eric G. Daub, Tom Dunstan, Thusal Bennett +30
We present FastNet version 1.0, a data-driven medium range numerical weather prediction (NWP) model based on a Graph Neural Network architecture, developed jointly between the Alan…
FastNet: Improving the physical consistency of machine-learning weather prediction models through loss function design
Tom Dunstan, Oliver Strickson, Thusal Bennett +31
Machine learning weather prediction (MLWP) models have demonstrated remarkable potential in delivering accurate forecasts at significantly reduced computational cost compared to tr…
Towards deployment-centric multimodal AI beyond vision and language
Xianyuan Liu, Jiayang Zhang, Shuo Zhou +45
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as h…
Environmental Sensor Placement with Convolutional Gaussian Neural Processes
Tom R. Andersson, Wessel P. Bruinsma, Stratis Markou +8
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 infor…
Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data
Bradley Gram-Hansen, Patrick Helber, Indhu Varatharajan +4
Informal settlements are home to the most socially and economically vulnerable people on the planet. In order to deliver effective economic and social aid, non-government organizat…