Publikationen von Matthias Rupp
Alle Typen
Vortrag (36)
21.
Vortrag
Kernel Methods in Machine Learning. Hands-On DFT and Beyond: Frontiers of Advanced Electronic Structure and Molecular Dynamics Methods, Beijing, China (2018)
22.
Vortrag
High-Throughput Energy Predictions for Molecules and Materials via Machine Learning. Workshop: Modern Approaches to Coupling Scales in Materials Simulations, Lenggries, Germany (2018)
23.
Vortrag
Machine Learning for Interpolation of Electronic Structure Calculations. The First International Conference on Machine Learning and Physics, Beijing, China (2018)
24.
Vortrag
The Many-Body Tensor Representation. CECAM Workshop, Machine Learning at Interfaces, EPFL, Lausanne, Switzerland (2018)
25.
Vortrag
Accurate Energy Predictions for Materials. International Workshop, Machine Learning for Quantum Many-body Physics, Max Planck Institute for the Physics of Complex Systems, Dresden, Germany (2018)
26.
Vortrag
Kernel-Based Machine Learning for Materials. BiGmax Workshop 2018 on Big-Data-Driven Materials Science, Kloster Irsee, Irsee, Germany (2018)
27.
Vortrag
Machine Learning for Materials. TMS 2018, 147th Annual Meeting & Exhibition, The Minerals, Metals & Materials Society, Phoenix, AZ, USA (2018)
28.
Vortrag
Machine Learning for Molecules and Materials: Potential and Limitations of Data-Driven Chemistry. 27th Austin Symposium on Molecular Structure and Dynamics, ASMD, Dallas, TX, USA (2018)
29.
Vortrag
Machine Learning for Quantum Mechanics: Interpolation of Electronic Structure Calculations. Seminar, Los Alamos National Laboratory, Los Alamos, NM, USA (2018)
30.
Vortrag
Machine Learning for Quantum Mechanics. Data Science Workshop, Scuola Internazionale Superiore di Studi Avanzati, SISSA, Trieste, Italy (2018)
31.
Vortrag
Interpolation of Electronic Structure Calculations via Machine Learning. International Workshop on Atomic Physics 2017, Dresden, Germany (2017)
32.
Vortrag
Machine Learning for Interpolation of Electronic Structure Calculations. Seminar, Department of Thin Films and Nanostructures, Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic (2017)
33.
Vortrag
Machine Learning for Quantum Mechanics. Hands-on Workshop Density-Functional Theory and Beyond: Accuracy, Efficiency and Reproducibility in Computational Materials Science, Berlin, Germany (2017)
34.
Vortrag
Unified Representation for Machine Learning of Molecules and Crystals. Workshop on Machine Learning and Many-Body Physics, Beijing, China (2017)
35.
Vortrag
Many-Body Tensor Representation. Working Conference on Materials and Data Analysis, CMSA Harvard University, Cambridge, MA, USA (2017)
36.
Vortrag
Many-Body Tensor Representation for Machine Learning of Materials. APS March Meeting 2017, New Orleans, LA, USA (2017)
37.
Vortrag
Accurate Machine Learning Predictions for Materials Properties. Workshop on Machine Learning Strategies for Materials Science, Aalto, Finland (2017)
38.
Vortrag
Many-Body Tensor Representation for Machine Learning of Solids. 57th Sanibel Symposium, St. Simons Island, GA, USA (2017)
39.
Vortrag
Understanding Many-Particle Systems with Machine Learning. Workshop, Institute for Pure and Applied Mathematics (IPAM), Lake Arrowhead, CA, USA (2016)
40.
Vortrag
New Data, Validation, Code and Representation for Interpolation Across Chemical Compound Space. IPAM Workshop on Machine Learning Meets Many-Particle Problems, Los Angeles, CA, USA (2016)