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KCDS Virtual Open House - Project 04 Exploring the Potential of machine learning methods for improving operational hydrological forecasting and prediction (EPOforHydro)

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Autor

Uwe Ehret, Sebastian Krumscheid

Herausgeber

Angela Hühnerfuß

Beteiligtes Institut

KIT-Zentrum Mathematik in den Natur-, Ingenieur- und Wirtschaftswissenschaften (KIT-Zentrum MathSEE)
Institut für Wasser und Gewässerentwicklung (IWG)
Scientific Computing Center (SCC)

Genre

Veranstaltung

Beschreibung

Meet KIT Graduate School Computational and Data Science in our virtual open house! Find out more about the graduate school and current doctoral projects.

Laufzeit (hh:mm:ss)

00:05:05

Serie

KCDS Virtual Open House

Publiziert am

31.03.2023

Fachgebiet

Informatik

Lizenz

Creative Commons Namensnennung – Nicht kommerziell – Weitergabe unter gleichen Bedingungen 4.0 International

Auflösung 1280 x 720 Pixel
Seitenverhältnis 16:9
Audiobitrate 66529 bps
Audio Kanäle 1
Audio Codec aac
Audio Abtastrate 48000 Hz
Gesamtbitrate 478019 bps
Container mov,mp4,m4a,3gp,3g2,mj2
Dauer 304.662000 s
Dateiname DIVA-2023-28_mp4.mp4
Dateigröße 18.204.285 byte
Bildwiederholfrequenz 25
Videobitrate 405456 bps
Video Codec h264

Embed-Code

KCDS Virtual Open House Folgen 1-7 von 7
KCDS Virtual Open House - Introduction and presentation of KCDS
KCDS Virtual Open House - Introduction and presentation of KCDS
KCDS Virtual Open House - Project 04 Exploring the Potential of machine learning methods for improving operational hydrological forecasting and prediction (EPOforHydro)
KCDS Virtual Open House - Project 04 Exploring the Potential of machine learning methods for improving operational hydrological forecasting and prediction (EPOforHydro)
KCDS Virtual Open House - Project 03 Optimization and acceleration of aerosol dynamics and chemistry subprocesses in weather and climate models
KCDS Virtual Open House - Project 03 Optimization and acceleration of aerosol dynamics and chemistry subprocesses in weather and climate models
KCDS Virtual Open House - Project 02 Deep Boltzmann - Structure-preserving deep neural networks to accelerate the solution of the Boltzmann equation
KCDS Virtual Open House - Project 02 Deep Boltzmann - Structure-preserving deep neural networks to accelerate the solution of the Boltzmann equation
KCDS Virtual Open House - Project 01 Logics for dynamical systems and practical theorem proving tools
KCDS Virtual Open House - Project 01 Logics for dynamical systems and practical theorem proving tools
KCDS Virtual Open House - How To Apply to KCDS
KCDS Virtual Open House - How To Apply to KCDS
KCDS Virtual Open House - Project 06 Theoretical and Empirical Analysis of Matheuristics
KCDS Virtual Open House - Project 06 Theoretical and Empirical Analysis of Matheuristics