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arXiv:2601. 03673v2 Announce Type: replace-cross Abstract: Physics-Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data.

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Modelling magnetic material properties with uncertainty-aware neural networks

arXiv:2606. 11870v1 Announce Type: cross Abstract: Machine learning is increasingly applied to accelerate the discovery of novel materials by exploring large compositional and structural design spaces.

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arXiv Machine Learning

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Neural Feature Governance: Extending Atom Prevalence

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arXiv Machine Learning

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SPLIT-PINN: Separable Probability Learning Technique via Physics-Informed Neural Networks for High-Dimensional Probabilistic Modeling

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Uncertainty quantification for trustworthy deep learning: Methods and measures

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