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  - **Homepage:** [matpes.ai](http://matpes.ai)
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  - **Paper:** [Preprint](https://doi.org/10.48550/arXiv.2503.04070)
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  - **Leaderboard:** [MatCalc-Benchmark](http://matpes.ai/benchmarks)
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- - **Point of Contact:** [Materials Virtual Lab](mailto:[email protected])
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  ### Dataset Summary
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  Machine Learning) packages, the [MatPES] (Materials Potential Energy Surface) dataset, and the [MatCalc] (Materials
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  Calculator).
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  - **Homepage:** [matpes.ai](http://matpes.ai)
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  - **Paper:** [Preprint](https://doi.org/10.48550/arXiv.2503.04070)
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  - **Leaderboard:** [MatCalc-Benchmark](http://matpes.ai/benchmarks)
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+ - **Point of Contact:** [Materials Virtual Lab]
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  ### Dataset Summary
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  Machine Learning) packages, the [MatPES] (Materials Potential Energy Surface) dataset, and the [MatCalc] (Materials
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  Calculator).
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+
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+ [Materials Virtual Lab]: http://materialsvirtuallab.org
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+ [Materials Project]: https://materialsproject.org
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+ [M3GNet]: http://dx.doi.org/10.1038/s43588-022-00349-3
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+ [CHGNet]: http://doi.org/10.1038/s42256-023-00716-3
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+ [TensorNet]: https://arxiv.org/abs/2306.06482
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+ [DIRECT]: https//doi.org/10.1038/s41524-024-01227-4
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+ [maml]: https://materialsvirtuallab.github.io/maml/
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+ [MatGL]: https://matgl.ai
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+ [MatPES]: https://matpes.ai
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+ [MatCalc]: https://matcalc.ai