activity
20222026
most citedAardvark weather: end-to-end data-driven weather forecasting

8 citations · 16 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

WeatherNext 3: Increasing resolution and performance of global weather models with raw observations

Stephan Rasp, Boris Babenko, Dominic Masters +22

State-of-the-art AI weather models have shown impressive medium-range forecast skill and computational efficiency, but suffer two key shortcomings: their forecasts have lower spati…

cs.LG2025★ 3 cited

Skillful joint probabilistic weather forecasting from marginals

Ferran Alet, Ilan Price, Andrew El-Kadi +8

Machine learning (ML)-based weather models have rapidly risen to prominence due to their greater accuracy and speed than traditional forecasts based on numerical weather prediction…

physics.ao-ph2024★ 8 cited

Aardvark weather: end-to-end data-driven weather forecasting

Anna Vaughan, Stratis Markou, Will Tebbutt +8

Weather forecasting is critical for a range of human activities including transportation, agriculture, industry, as well as the safety of the general public. Machine learning model…

cs.LG2023

Sim2Real for Environmental Neural Processes

Jonas Scholz, Tom R. Andersson, Anna Vaughan +2

Machine learning (ML)-based weather models have recently undergone rapid improvements. These models are typically trained on gridded reanalysis data from numerical data assimilatio…

stat.ML2023★ 3 cited

Autoregressive Conditional Neural Processes

Wessel P. Bruinsma, Stratis Markou, James Requiema +6

Conditional neural processes (CNPs; Garnelo et al., 2018a) are attractive meta-learning models which produce well-calibrated predictions and are trainable via a simple maximum like…

stat.ML2022★ 2 cited

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…

stat.ML2022

Ice Core Dating using Probabilistic Programming

Aditya Ravuri, Tom R. Andersson, Ieva Kazlauskaite +5

Ice cores record crucial information about past climate. However, before ice core data can have scientific value, the chronology must be inferred by estimating the age as a functio…