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1

Application of batch learning for boosting high-throughput ab initio success rates and reducing computational effort required using data-driven processes

Hilgers, Robin
2023

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2

Machine Learning-based estimation and explainable artificial intelligence-supported interpretation of the critical temperature from magnetic ab initio Heusler alloys data

Hilgers, Robin
2023

2023

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3

Conference Presentation

Magnetic Multilayers: From High-Throughput Ab-initio Calculations to Predictive Machine Learning

Hilgers, Robin
2023

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4

Application of Machine-Learning Models and XAI in Materials Science Using Magnetic DFT Data

Hilgers, Robin
2023

OpenAccess

5

Best of Atomistic Machine Learning

Wasmer, Johannes
2023

“...atomistic-machine-learning Other...”

6

Machine Learning Emulators for First-Principles Simulations of Quantum Materials

Wasmer, Johannes
2023

“...machine learning Other...”
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7

Code collection for machine learning assisted materials screening in the search for novel half-metallic Heusler alloys

Hilgers, Robin
2023

8

Workflow, data processing, data analysis and predictive ML scripts used for DFT-integrated machine learning methodology in combination with the FLAPW code FLEUR

Hilgers, Robin
2023

9

Conference Presentation

Curie Temperature Prediction Models of Magnetic Heusler Alloys Using Machine Learning Methods Based on First-Principles Data From Ab-initio KKR-GF Calculations

Hilgers, Robin
2023

OpenAccess

10

ML-ready Curie temperatures and descriptors extracted from the JuHemd database

Hilgers, Robin
2022

2022 (2022) S. 174

“...Machine learning Other...”

11

SiSc Lab 2022, Project 6. A machine learning playground in quantum mechanical simulation.

Wasmer, Johannes
2022

12

Comparison of structural representations for machine learning-enhanced DFT of impurity embeddings

Wasmer, Johannes
2022

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13

Development of a surrogate machine learning model for the acceleration of density functional calculations with the Korringa-Kohn-Rostoker method

Wasmer, Johannes
2021

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14

Comparison of structural representations for machine learning-accelerated ab initio calculations

Wasmer, Johannes
2021

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