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20232025
most citedOn-the-Fly Fine-Tuning of Foundational Neural Network Potentials: A Bayesian Neural Network Approach

2 citations · 4 across the 4 of their papers we have counts for

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cond-mat.mtrl-sci2023

Position Paper on Materials Design -- A Modern Approach

Willi Grossmann, Sebastian Eilermann, Tim Rensmeyer +4

Traditional design cycles for new materials and assemblies have two fundamental drawbacks. The underlying physical relationships are often too complex to be precisely calculated an…

physics.chem-ph2023★ 1 cited

High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks

Tim Rensmeyer, Benjamin Craig, Denis Kramer +1

Even though Bayesian neural networks offer a promising framework for modeling uncertainty, active learning and incorporating prior physical knowledge, few applications of them can…