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Uk

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Preprint Oct 2026

The mass discrepancy problem in massive stars: an inferential perspective

Bayesian inference has become a standard tool for inferring stellar parameters from stellar evolution models. However, comparatively little attention has been paid to how alternative Bayesian likelihood formulations influence inferred stellar parameters, and the resulting evolutionary mass discrepancy for massive main...

C. I. Eze, G. Handler, M. Vanrespaille et al. · 0 citations

#small language model Preprint Aug 2026

uMOF: A Universal Database, Benchmark, and Machine Learning Interatomic Potentials for Metal-Organic Frameworks

Foundation machine learning interatomic potentials (MLIPs) deliver near-ab-initio accuracy at a fraction of the computational cost, yet their promise for Metal-organic Frameworks (MOFs) remains largely unrealized as large unit cells make first-principles training data expensive to generate, fine-tuned models are scarce...

T. J. Inizan, Prathami Divakar Kamath, Alin M. Elena et al. · 0 citations