Authors: George Rajna
Machine learning has been used by scientists in the US to reduce unwanted fluctuations in photon beams from a synchrotron light source.  There may not be an obvious connection between rewilding and machine learning, but as highlighted today at ESA's ɸ-week, a project in the Netherlands uses satellite data and new digital technology to understand how a nature reserve responds to the pressure of being grazed by herbivores.  At the University of South Florida, researchers are integrating machine learning techniques into their work studying proteins.  Bioinformatics professors Anthony Gitter and Casey Greene set out in summer 2016 to write a paper about biomedical applications for deep learning, a hot new artificial intelligence field striving to mimic the neural networks of the human brain.  A team of researchers from the University of Muenster in Germany has now demonstrated that this combination is extremely well suited to planning chemical syntheses-so-called retrosyntheses-with unprecedented efficiency.  Two physicists at ETH Zurich and the Hebrew University of Jerusalem have developed a novel machine-learning algorithm that analyses large data sets describing a physical system and extract from them the essential information needed to understand the underlying physics. 
Comments: 34 Pages.
[v1] 2019-11-28 03:21:46
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