July 3, 2020

Forecasting the weather with neural ODEs

Weather forecasting is a tricky problem. Traditionally, it has been done by manually modelling weather dynamics using differential equations, but this approach is highly dependent on us getting the equations right. To avoid this problem, we can use machine learning to directly predict the weather, which let’s us make predictions without modelling the dynamics. However, this approach requires huge amounts of data to reach good performance. Fortunately, there is a middle ground: What if we instead use machine learning to model the dynamics of the weather? Read more

© Sebastian Callh 2020