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Spatial Reasoning in Random Field Models: Part II

Spatial Reasoning in Random Field Models: Part II

In Part I of this series, we discussed the mathematics underpinning Gaussian process (GP) and Gaussian random field (GRF) models, how they…
Go to the profile of Rachel Prudden
Rachel Prudden
Impact Lab Data Science Events

Impact Lab Data Science Events

The Environmental Futures & Big Data Impact Lab is a partnership of seven organisations, including the Met Office and the University of…
Go to the profile of Stephen Haddad
Stephen Haddad
Spatial Reasoning in Random Field Models: Part I

Spatial Reasoning in Random Field Models: Part I

Gaussian processes (GPs) are a probabilistic model used for a wide range of ML and stats. They appear in many different contexts including…
Go to the profile of Rachel Prudden
Rachel Prudden
You do you

You do you

How next-gen data platforms stop weather and climate scientists from being software engineers and focus on science.
Go to the profile of Theo McCaie
Theo McCaie
Metadata Queries

Metadata Queries

Another option for user interactions with large datasets
Go to the profile of Peter Killick
Peter Killick
Probabilistic programming for event detection

Probabilistic programming for event detection

Imagine you are a scientist, studying a particular kind of event: perhaps a volcanic eruption or a lightning strike. You have some data in…
Go to the profile of Rachel Prudden
Rachel Prudden
Representing thousands of NetCDF Files using TileDB

Representing thousands of NetCDF Files using TileDB

This blog post supports a poster that I presented at AGU2020. You can find the poster here. Note: the QR code in the poster links to this…
Go to the profile of Peter Killick
Peter Killick
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