Publications (7)
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…
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…
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…
Generating Material Maps to Map Informal Settlements
Patrick Helber, Bradley Gram-Hansen, Indhu Varatharajan +4
Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals. This is because informal settlements are home to the most social…