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Scientific Computing and Machine Learning
SCML
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AI

Aznaur Aliev

M.S. Student

AI Deep learning Computer Vision Reinforcement Learning

Mhd. Emad Alolaby

Associate Editor, King Abdullah University of Science and Technology

Network Design telecommunication 5G networks GSM Digital Communications optical fiber AI deep learning MATLAB

Mohammed A Shukri

Consultant (former), King Abdullah University of Science and Technology

Neural Networks AI Python BLE communication

Technical Consultant at KAUST (King Abdullah University of Science and Technology).

Models, Methods, Applications: HPC in Medicine, Science, Engineering, and AI

Rolf Krause, Professor, Applied Mathematics and Computational Sciences
May 14, 16:00 - 17:00

B3 L5 R5209

machine learning medicine AI

Abstract The accurate numerical prediction of complex processes in medicine, science, and engineering requires a well balanced interplay of mathematical models, numerical methods, and scientific software. In this talk, we discuss along different examples from engineering, earth-sciences, and medicine the various challenges in building predictive models. Our focus will be on the algorithmic aspects, i.e. on the numerical methods, -may it be finite elements or neural networks in the context of massive parallelism. We will present in particular parallel preconditioners for non-linear problems

Scientific Computing and Machine Learning (SCML)

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