Publications of Matthias Scheffler
All genres
Thesis - Diploma (1)
Thesis - Diploma
Polymerization of Carbon Nitride - experimental and theoretical investigation. Diploma, Freie Universität, Berlin (2006)
Thesis - Master (5)
Thesis - Master
Identifying descriptors for the in-silico, high-throughput discovery of the thermal insulators for thermoelectric applications. Master, Technische Universität, Darmstadt (2022)
Thesis - Master
Discussion, implementation and demonstration of AI-guided active workflows. Master, Technische Universität, Darmstadt (2021)
Thesis - Master
Identifying exceptional data points in materials science using machine learning. Master, Technische Universität, Berlin (2021)
Thesis - Master
First-principles Study of Thermoelectric Magnesium Silicides with High-Throughput Techniques. Master, Technische Universität, Berlin (2016)
Thesis - Master
Machine Learning of the Stability of Octet Binaries. Master, Technische Universität, Berlin (2016)
Thesis - Bachelor (1)
Thesis - Bachelor
Thermal Conductivities of Group IV and Group III-V Compound Semiconductors from First Principles. Bachelor, Technische Universität, Berlin (2018)
Working Paper (17)
Working Paper
Modelling the Time-Dependent Reactivity of Catalysts by Experiments and Artificial Intelligence. (2025)
Working Paper
Materials-Discovery Workflows Guided by Symbolic Regression: Identifying Acid-Stable Oxides for Electrocatalysis. (2024)
Working Paper
Workflows for Artificial Intelligence. (2024)
Working Paper
Temperature-Dependent Electronic Spectral Functions From Band-Structure Unfolding. (2024)
Working Paper
Coupled-Cluster Theory for the Ground State and for Excitations. (2024)
Working Paper
Accelerating the Training and Improving the Reliability of Machine-Learned Interatomic Potentials for Strongly Anharmonic Materials Through Active Learning. (2024)
Working Paper
Coherent Collections of Rules Describing Exceptional Materials Identified with a Multi-Objective Optimization of Subgroups. (2024)
Working Paper
From Prediction to Action: The Critical Role of Proper Performance Estimation for Machine-Learning-Driven Materials Discovery. (2023)
Working Paper
Towards a Multi-Objective Optimization of Subgroups for the Discovery of Materials with Exceptional Performance. (2023)
Working Paper
On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials. (2023)
Working Paper
Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models. (2023)
Working Paper
Learning Rules for Materials Properties and Functions. (2021)
Working Paper
Ab initio data-analytics study of carbon-dioxide activation on semiconductor oxide surfaces. (2019)