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Presentation Open Access

Learning with Graph Kernels in the Chemical Universe

Tang, Yu-Hang


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    "description": "<p>Presentations slides of <a href=\"https://crd.lbl.gov/departments/computational-science/ccmc/staff/alvarez-fellows/yu-hang-tang/\">Yu-Hang Tang</a>&nbsp;during the 2019 <a href=\"https://data-science.llnl.gov/latest/workshop-2019#Day%202\">DSI Data Science Workshop</a>&nbsp;on application of active machine learning and graph kernels. The talk also features the release of the <a href=\"https://pypi.org/project/graphdot/\">GraphDot</a> library.</p>", 
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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"
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