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Author

Kamal Choudhary

2 papers indexed here

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Open access Sep 2026

When code does not run: reproducibility challenges in materials machine learning benchmarks

Reproducible benchmarks are essential for advancing data-driven materials research by standardizing datasets, prediction tasks, and evaluation protocols. In machine learning benchmarks, reproducibility is often assumed to follow from releasing source code and documented software dependencies. However, dependency specif...

Bohui Lyu, J. Bonini, Mao Zhang et al. · 0 citations
Preprint Sep 2026

ALIGNN 2.0: A Unified Line-Graph Neural Network Framework for Materials Screening, Force Fields, Inverse Design, Spectroscopy, and Microscopy

Graph neural networks are central to materials property prediction and machine-learning interatomic potentials, yet their reliance on specialized graph libraries hampers portability and reproducibility, and property and force-field models have historically required separate graph pipelines. We present ALIGNN 2.0, a dep...

Jaehyung Lee, C. R. Campbell, Akshaya Ajith et al. · 0 citations

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