Regensburg 2019 – wissenschaftliches Programm

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MM: Fachverband Metall- und Materialphysik

MM 37: Topical session (Symposium MM): Big Data Analytics in Materials Science

Donnerstag, 4. April 2019, 15:00–18:45, H43

Sessions: Big Data Analytics in Materials Science III and IV

15:00 MM 37.1 Topical Talk: Atomistic Machine Learning between Physics and DataMichele Ceriotti and •Michael Willatt
15:30 MM 37.2 Atomic cluster expansion for accurate and transferable interatomic potentials — •Ralf Drautz
15:45 MM 37.3 Simultaneous and Reinforced Learning of Materials Properties from Incomplete Databases with Multi-Task SISSO — •Emre Ahmetcik, Runhai Ouyang, Christian Carbogno, Matthias Scheffler, and Luca M. Ghiringhelli
16:00 MM 37.4 Information-theoretic Feature Selection and its Applications in Materials Science — •Benjamin Regler, Matthias Scheffler, and Luca M. Ghiringhelli
16:15 MM 37.5 The speech of strangers in material science — •Juliana Schell, Peter Schaaf, Hans-Christian Hofsäss, and Doru C. Lupascu
  16:30 15 min. break
16:45 MM 37.6 Topical Talk: High-throughput with Particle Technology — •Lutz Mädler
17:15 MM 37.7 Topical Talk: Microstructure is the know-it-all - classification approaches with data mining and deep learning methods — •Frank Mücklich and Dominik Britz
17:45 MM 37.8 Electronic density-of-states fingerprints for finding similar materials — •Martin Kuban, Santiago Rigamonti, Markus Scheidgen, and Claudia Draxl
18:00 MM 37.9 Accurate Thermal Conductivities of Complex, Strongly-Anharmonic Solids — •Florian Knoop, Thomas Purcell, Marcel Hülsberg, Matthias Scheffler, and Christian Carbogno
18:15 MM 37.10 Surface Structure Search using Coarse Grained Modeling and Bayesian Linear Regression — •Lukas Hörmann, Andreas Jeindl, Alexander T. Egger, and Oliver T. Hofmann
18:30 MM 37.11 Predicting Reaction Energetics with Machine Learning — •Sina Stocker, Johannes T. Margraf, and Karsten Reuter
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DPG-Physik > DPG-Verhandlungen > 2019 > Regensburg