Publications of Matthias Rupp

Rupp, M.: Kernel Methods in Machine Learning. Hands-On DFT and Beyond: Frontiers of Advanced Electronic Structure and Molecular Dynamics Methods, Beijing, China (2018)

Rupp, M.: High-Throughput Energy Predictions for Molecules and Materials via Machine Learning. Workshop: Modern Approaches to Coupling Scales in Materials Simulations, Lenggries, Germany (2018)

Rupp, M.: Machine Learning for Interpolation of Electronic Structure Calculations. The First International Conference on Machine Learning and Physics, Beijing, China (2018)

Rupp, M.: The Many-Body Tensor Representation. CECAM Workshop, Machine Learning at Interfaces, EPFL, Lausanne, Switzerland (2018)

Rupp, M.: 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)

Rupp, M.: Kernel-Based Machine Learning for Materials. BiGmax Workshop 2018 on Big-Data-Driven Materials Science, Kloster Irsee, Irsee, Germany (2018)

Rupp, M.: Machine Learning for Materials. TMS 2018, 147th Annual Meeting & Exhibition, The Minerals, Metals & Materials Society, Phoenix, AZ, USA (2018)

Rupp, M.: 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)

Rupp, M.: Machine Learning for Quantum Mechanics: Interpolation of Electronic Structure Calculations. Seminar, Los Alamos National Laboratory, Los Alamos, NM, USA (2018)

Rupp, M.: Machine Learning for Quantum Mechanics. Data Science Workshop, Scuola Internazionale Superiore di Studi Avanzati, SISSA, Trieste, Italy (2018)

Rupp, M.: Interpolation of Electronic Structure Calculations via Machine Learning. International Workshop on Atomic Physics 2017, Dresden, Germany (2017)

Rupp, M.: 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)

Rupp, M.: Machine Learning for Quantum Mechanics. Hands-on Workshop Density-Functional Theory and Beyond: Accuracy, Efficiency and Reproducibility in Computational Materials Science, Berlin, Germany (2017)

Rupp, M.: Unified Representation for Machine Learning of Molecules and Crystals. Workshop on Machine Learning and Many-Body Physics, Beijing, China (2017)

Rupp, M.: Many-Body Tensor Representation. Working Conference on Materials and Data Analysis, CMSA Harvard University, Cambridge, MA, USA (2017)

Rupp, M.: Many-Body Tensor Representation for Machine Learning of Materials. APS March Meeting 2017, New Orleans, LA, USA (2017)

Rupp, M.: Accurate Machine Learning Predictions for Materials Properties. Workshop on Machine Learning Strategies for Materials Science, Aalto, Finland (2017)

Rupp, M.: Many-Body Tensor Representation for Machine Learning of Solids. 57th Sanibel Symposium, St. Simons Island, GA, USA (2017)

Rupp, M.: Understanding Many-Particle Systems with Machine Learning. Workshop, Institute for Pure and Applied Mathematics (IPAM), Lake Arrowhead, CA, USA (2016)

Rupp, M.: 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)