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Vibrational power spectra as a tool to benchmark universal machine-learning interatomic potentials for molecular systems: the OMOL-1k-MD data set - Nature
Vibrational power spectra as a tool to benchmark universal machine-learning interatomic potentials for molecular systems: the OMOL-1k-MD data set Nature
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- PossiblePossibly related (embedding) · 65%Active rejection enables reliable generalization of universal machine-learning interatomic potentials →
- PossiblePossibly related (embedding) · 56%light-and-molecules/melts →
- PossiblePossibly related (embedding) · 54%Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark →
- PossiblePossibly related (embedding) · 51%arogozhnikov/hep_ml →
- PossiblePossibly related (embedding) · 50%electrocatalysis-group/atomic-recipes →
- PossiblePossibly related (embedding) · 55%Universal Thermodynamic Interatomic Potentials for Crystalline Materials →
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paperBeyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmarkrepoarogozhnikov/hep_mlrepoelectrocatalysis-group/atomic-recipespaperActive rejection enables reliable generalization of universal machine-learning interatomic potentialsrepolight-and-molecules/meltspaperUniversal Thermodynamic Interatomic Potentials for Crystalline Materials