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Dresden 2020 – scientific programme

The DPG Spring Meeting in Dresden had to be cancelled! Read more ...

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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 103: Topical Session: Data Driven Materials Science - Machine Learning for Materials Characterization (joint session MM/CPP)

Thursday, March 19, 2020, 15:45–17:15, BAR 205

15:45 CPP 103.1 Topical Talk: Machine learning tools in analyticat transmission electron microscopy — •Cécile Hébert and Hui Chen
16:15 CPP 103.2 Automatic semantic segmentation of Scanning Transmission Electron Microscopy (STEM) images using an unsupervised machine learning approach — •Ning Wang, Christoph Freysoldt, Christian Liebscher, and Jörg Neugebauer
16:30 CPP 103.3 Bayesian models and machine-learning for NMR crystal structure determinations — •Edgar Albert Engel, Andrea Anelli, Albert Hofstetter, Federico Maria Paruzzo, Lyndon Emsley, and Michele Ceriotti
16:45 CPP 103.4 Teaching machines to learn dynamics in NMR observables — •Arobendo Mondal, Karsten Reuter, and Christoph Scheurer
17:00 CPP 103.5 Automatic Identification of Crystallographic Interfaces from Scanning Transmission Electron Microscopy Data by Artificial Intelligence — •Byung Chul Yeo, Christian H. Liebscher, Matthias Scheffler, and Luca Ghiringhelli
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