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Published August 8, 2019 | Version v1
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Learning with Graph Kernels in the Chemical Universe

Creators

  • 1. Lawrence Berkeley National Laboratory

Description

Presentations slides of Yu-Hang Tang during the 2019 DSI Data Science Workshop on application of active machine learning and graph kernels. The talk also features the release of the GraphDot library.

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Graph-Kernels-Chemical-Universe.pdf

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References

  • Tang, Y. H., & de Jong, W. A. (2019). Prediction of atomization energy using graph kernel and active learning. The Journal of chemical physics, 150(4), 044107. https://doi.org/10.1063/1.5078640