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Deep generative nowcasting: Nature publication

Deep generative nowcasting: Nature publication

We are happy to announce that our collaboration with Google DeepMind on applying deep learning techniques to precipitation nowcasting has…
Go to the profile of Rachel Prudden
Rachel Prudden
Using causal network theory as a scaffold for scientific intuition

Using causal network theory as a scaffold for scientific intuition

Climate scientists often use causal reasoning informally, but formalising it can have a couple of advantages. First, it makes it easier for…
Go to the profile of Ferhan Dack
Ferhan Dack
The State of Data Science for Earth Sciences

The State of Data Science for Earth Sciences

Report on ESIP 2021 Summer Meeting
Go to the profile of Stephen Haddad
Stephen Haddad
Probabilistic Reasoning (Seminar)

Probabilistic Reasoning (Seminar)

I recently had the opportunity to give a seminar as part of the Oxford ML and Physics seminar series. I talked about probabilistic…
Go to the profile of Rachel Prudden
Rachel Prudden
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
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