Publikationen von Matthias Rupp

Rupp, M.: Practical Tutorial on Machine Learning for Electronic Structure Calculations. IPAM Workshop on Understanding Many-Particle Systems with Machine Learning, Los Angeles, CA, USA (2016)

Rupp, M.: Challenges in Development of Accurate and Efficient Atomistic Machine Learning Models. CECAM Workshop, Big Data of Materials Science - Critical Next Steps, Lausanne, Switzerland (2015)

Rupp, M.: Machine Learning Models for Materials Science at the Atomic Scale. Seminar, National Institute for Materials Science (NIMS), Tsukuba, Japan (2015)

Rupp, M.: Predicting Results of Quantum Mechanical Calculations: Challenges for Machine Learning. Workshop, Frontiers in Data-Driven Science and Technology: Recent Advances in Machine Learning and Applications, Nagoya, Japan (2015)

Rupp, M.: Quantum Mechanical Properties of Atoms in Molecules via Machine Learning. Psi-k 2015 Conference, San Sebastian, Spain (2015)

Rupp, M.: Quantum Mechanics / Machine Learning Models. Hands-on Workshop Density-Functional Theory and Beyond: First-Principles Simulations of Molecules and Materials, Berlin, Germany (2015)

Rupp, M.: Machine Learning for Materials Science. IPAM Workshop on Materials for a Sustainable Energy Future, Reunion Meeting, Institute for Pure and Applied Mathematics, Lake Arrowhead, CA, USA (2015)

Rupp, M.: Representing Atoms in Molecules. CECAM/Psi-k Workshop, From Many-Body Hamiltonians to Machine Learning and Back, Berlin, Germany (2015)

Langer, M. F.: Machine Learning for Atomistic Modeling: Representations and Thermal Transport. Dissertation, Technische Universität, Berlin (2023)

Rupp, M.; von Lilienfeld, O. A.; Burke, K.: Special Topic on Data-Enabled Theoretical Chemistry. The Journal of Chemical Physics 148 (24), 241401 (2018)