Publications of Matthias Scheffler
All genres
Thesis - PhD (37)
861.
Thesis - PhD
Scheffler, M.: Winkelaufgelöste Photoemission von Adsorbatsystemen. Technische Universität Berlin Berlin
Thesis - Diploma (1)
862.
Thesis - Diploma
Cao, J.: Polymerization of Carbon Nitride - experimental and theoretical investigation. Freie Universität Berlin
Thesis - Master (5)
863.
Thesis - Master
Zhao, B.: Identifying descriptors for the in-silico, high-throughput discovery of the thermal insulators for thermoelectric applications. Technische Universität Darmstadt
864.
Thesis - Master
Lim, B.: Discussion, implementation and demonstration of AI-guided active workflows. Technische Universität Darmstadt
865.
Thesis - Master
Oehlers, M.: Identifying exceptional data points in materials science using machine learning. Technische Universität Berlin
866.
Thesis - Master
Kowalski, H.-H.: First-principles Study of Thermoelectric Magnesium Silicides with High-Throughput Techniques. Technische Universität Berlin
867.
Thesis - Master
Ahmetcik, E.: Machine Learning of the Stability of Octet Binaries. Technische Universität Berlin
Thesis - Bachelor (1)
868.
Thesis - Bachelor
: Thermal Conductivities of Group IV and Group III-V Compound Semiconductors from First Principles. Technische Universität Berlin
Working Paper (11)
869.
Working Paper
Foppa, L. and M. Scheffler: Coherent Collections of Rules Describing Exceptional Materials Identified with a Multi-Objective Optimization of Subgroups., in press.
870.
Working Paper
Kokott, S., , , C. Carbogno, , , , M. Scheffler and : Efficient All-electron Hybrid Density Functionals for Atomistic Simulations Beyond 10,000 Atoms., in press.
871.
Working Paper
L. Foppa and M. Scheffler: From Prediction to Action: The Critical Role of Proper Performance Estimation for Machine-Learning-Driven Materials Discovery., in press.
, , , , 872.
Working Paper
Foppa, L. and M. Scheffler: Towards a Multi-Objective Optimization of Subgroups for the Discovery of Materials with Exceptional Performance., in press.
873.
Working Paper
L.M. Ghiringhelli, C. Carbogno, and M. Scheffler: On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials., in press.
, 874.
Working Paper
Speckhard, D., C. Carbogno, L.M. Ghiringhelli, , M. Scheffler and : Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models., in press.
875.
Working Paper
M. Scheffler, , , , , , , and : Roadmap on Electronic Structure Codes in the Exascale Era., in press.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , 876.
Working Paper
M. Scheffler: Learning Rules for Materials Properties and Functions., in press.
and 877.
Working Paper
R. Ouyang, , M. Scheffler, L.M. Ghiringhelli and C. Carbogno: Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing., in press.
, 878.
Working Paper
M. Scheffler and : Three European Centers of Excellence in Computational Science. (133), 1–13 (2016).
, , , 879.
Working Paper
Ghiringhelli, L.M., C. Carbogno, S.V. Levchenko, F.R. Mohamed, , , and M. Scheffler: Towards a Common Format for Computational Materials Science Data. (131), 1–16 (2016).
Issue (1)
880.
Issue
Scheffler, M. and : Focus on Advances in Surface and Interface Science. New Journal of Physics 9 (2007).