Notices

1. Frederik Kratzert (kratzert@sigmoid.social)'s status on Friday, 02-Dec-2022 17:12:39 CET Frederik Kratzert

   2. Operational #flood #forecasting

   At Google, we are working towards a flood forecasting system with global coverage. Our models are already operational in several regions/countries of the world and I am happy to chat with people from the same area to exchange experiences and ideas related to operational modeling.

   • Frederik Kratzert (kratzert@sigmoid.social)'s status on Friday, 02-Dec-2022 17:12:38 CET Frederik Kratzert

     in reply to

     5. NeuralHydrology (#Python library)

     I'm a strong advocate of #reproducibility and #opensource software. As such, we open sourced our research library NeuralHydrology many years ago, trying to make our tools easily accessible to the wider community. If you are using NeuralHydrology in your research and have feedback/feature requests that you would like to share, please contact me.

     https://github.com/neuralhydrology/neuralhydrology

   • Frederik Kratzert (kratzert@sigmoid.social)'s status on Friday, 02-Dec-2022 17:12:39 CET Frederik Kratzert

     in reply to

     3. ML-based World/Landsurface models

     If you are working on machine learning based foundational/landsurface models I would be very happy to have a chat and to learn more about your research!

   • Frederik Kratzert (kratzert@sigmoid.social)'s status on Friday, 02-Dec-2022 17:12:39 CET Frederik Kratzert

     in reply to

     4. Explainable AI

     Trying to understand what ML-based models learn is interesting me for several years now. For example, why is the LSTM so much better in modeling the rainfall-runoff system than any physical/conceptual model, using the same input data? Is there anything we can learn from this model that we can then integrate into conceptual/physical models?

     Pybonacci repeated this.