Conveners
Scientific Computing, Machine Learning and large Data Management
- Derek Heinrich Feichtinger (Paul Scherrer Institut)
Description
Session 12
Machine learning (ML) approaches such as neural networks (NN) and Gaussian processes (GP) are powerful tools that can learn input-output models of complex systems directly from data. Because of their strengths ML methods have been growing in popularity in all areas of science and engineering. One limitation of such methods is that if the system which generated the training data changes with...
Wavefront sensing and characterization of the spatial and coherent properties of the Free-Electron-Lasers (FELs) radiation is vital for experiment planning, beamline optics alignment and the photon diagnostics. At the Free-electron LASer at Hamburg (FLASH), the Hartmann wavefront sensing is a typical technique used for the single-shot beam characterization. However, it is working in the...
Introduction
The ongoing developments in accelerators, detectors and experiment automation is leading to a rapid growth of data generated during experiments. A viable solution is utilizing suitable infrastructures that allow additional remote high performance capacity for processing and analysis of data from the experimental facilities with larger data volumes and higher processing...
