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01/25/2022
A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data
As the costs of sensors and associated IT infrastructure decreases - as ...
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08/17/2020
Bayesian deep learning for mapping via auxiliary information: a new era for geostatistics?
For geospatial modelling and mapping tasks, variants of kriging - the sp...
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05/06/2020
A framework for probabilistic weather forecast post-processing across models and lead times using machine learning
Forecasting the weather is an increasingly data intensive exercise. Nume...
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12/12/2019
A Hierarchical Modelling Framework for Correcting Delayed Reporting in Spatio-Temporal Disease Surveillance Data
Delayed reporting is a well established problem in the surveillance of i...
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06/10/2019
An Advanced Hidden Markov Model for Hourly Rainfall Time Series
For hydrological applications, such as urban flood modelling, it is ofte...
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06/10/2019
A Comprehensive Hidden Markov Model for Hourly Rainfall Time Series
For hydrological applications, such as urban flood modelling, it is ofte...
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04/06/2019
Multivariate Hierarchical Frameworks for Modelling Delayed Reporting in Count Data
In many fields and applications count data can be subject to delayed rep...
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01/09/2019
Estimating Global Household Air Pollution: A Multivariate Hierarchical Model for Cooking Fuel Prevalence
Globally, an estimated 3.8 million deaths per year can be attributed to ...
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09/03/2018