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Found 3 papers, 2 papers with code
Augmenting x-ray single particle imaging reconstruction with self-supervised machine learning
The development of X-ray Free Electron Lasers (XFELs) has opened numerous opportunities to probe atomic structure and ultrafast dynamics of various materials.
Machine learning enabled experimental design and parameter estimation for ultrafast spin dynamics
Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and material physics, which often suffer from the scarcity of facility resources and increasing complexities.
Capturing dynamical correlations using implicit neural representations
The observation and description of collective excitations in solids is a fundamental issue when seeking to understand the physics of a many-body system.
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