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KCDS How to prepare your application
KCDS How to prepare your application
Angela Hühnerfuß
Project 03: Mathematical Foundations of Bayesian Neural Networks
Project 03: Mathematical Foundations of Bayesian Neural Networks
Charlotte Debus, Sebastian Krumscheid
Project 02: Advanced Parallelization Techniques for datadriven Uncertainty Quantification
Project 02: Advanced Parallelization Techniques for datadriven Uncertainty Quantification
Sebastian Krumscheid, Linus Seelinger
Project 04: Replacement of physical PSC simulation by machine learning in an Earth system model
Project 04: Replacement of physical PSC simulation by machine learning in an Earth system model
Ole Kirner, Jörg Meyer, Achim Streit
Grenzenlose Forschung
Grenzenlose Forschung
Adrian Yass
Project 01: Scholars in the loop? Bridging the gap between distinctive knowledge of small disciplines and training data for AI
Project 01: Scholars in the loop? Bridging the gap between distinctive knowledge of small disciplines and training data for AI
Germaine Götzelmann, Danah Tonne, Charlotte Debus
Wir sind gut organisiert
Wir sind gut organisiert
Adrian Yass, Tatjana Schwarzbeck
Nerds Retten die Welt - Wissenschaftsperformance am KIT
Nerds Retten die Welt - Wissenschaftsperformance am KIT
Adrian Yass
Stadtradeln 2023
Stadtradeln 2023
Adrian Yass
Tag der offenen Tür des KIT 2023
Tag der offenen Tür des KIT 2023
Adrian Yass
KCDS Talk: "How the brain works and why adaptive models matter" (Dr. Cihan Ates)
KCDS Talk: "How the brain works and why adaptive models matter" (Dr. Cihan Ates)
Cihan Ates
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
Ugur Cayoglu
KCDS Virtual Open House - Introduction and presentation of KCDS
KCDS Virtual Open House - Introduction and presentation of KCDS
Uwe Ehret
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)
Uwe Ehret, Sebastian Krumscheid
KCDS Virtual Open House - How To Apply to KCDS
KCDS Virtual Open House - How To Apply to KCDS
Angela Hühnerfuß
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
André Platzer
KCDS Virtual Open House - Project 06 Theoretical and Empirical Analysis of Matheuristics
KCDS Virtual Open House - Project 06 Theoretical and Empirical Analysis of Matheuristics
John Alasdair Warwicker, Marion Baumann
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
Martin Frank