Frederik Kratzert, Google: Long Short-Term Memory networks (LSTMs) for rainfall-runoff modeling
På RISE Learning Machines Seminar den 10 november ger Fredrik Kratzert från Google sin presentation: " Long Short-Term Memory networks (LSTMs) for rainfall-runoff modeling"
– In this talk, I will talk about my research over the last few years on LSTMs for rainfall-runoff modelling.
Seminariet är på engelska.
Abstract
In this talk, I will talk about my research over the last few years on LSTMs for rainfall-runoff modelling. We will cover a short introduction about the model, talk about why it is such a good fit for this application, and I will share insights from various studies of the recent past. Additionally, we will revisit the best practices that you should follow, in case you are interested in applying LSTMs in your research/work.
Om talaren
Frederik did his Master in environmental engineering and his PhD in machine learning with a focus on the intersection of these two fields. After his PhD, Frederik joined Google as a visiting faculty researcher, where he is working in Google’s Flood Forecasting team, building a global flood warning system.