American Chemical Society (ACS)
Interpretable Molecular Property Predictions Using Marginalized Graph Kernels
Publication
, Preprint
Xiang, Y; Tang, Y-H; Lin, G; Reker, D
February 20, 2023
Duke Scholars
Altmetric Attention Stats
Dimensions Citation Stats
Citation
APA
Chicago
ICMJE
MLA
NLM
Xiang, Y., Tang, Y.-H., Lin, G., & Reker, D. (2023). Interpretable Molecular Property Predictions Using Marginalized Graph Kernels. American Chemical Society (ACS). https://doi.org/10.26434/chemrxiv-2023-gd1gl
Xiang, Yan, Yu-Hang Tang, Guang Lin, and Daniel Reker. “Interpretable Molecular Property Predictions Using Marginalized Graph Kernels.” American Chemical Society (ACS), February 20, 2023. https://doi.org/10.26434/chemrxiv-2023-gd1gl.
Xiang Y, Tang Y-H, Lin G, Reker D. Interpretable Molecular Property Predictions Using Marginalized Graph Kernels. American Chemical Society (ACS). 2023.
Xiang, Yan, et al. “Interpretable Molecular Property Predictions Using Marginalized Graph Kernels.” American Chemical Society (ACS), 20 Feb. 2023. Crossref, doi:10.26434/chemrxiv-2023-gd1gl.
Xiang Y, Tang Y-H, Lin G, Reker D. Interpretable Molecular Property Predictions Using Marginalized Graph Kernels. American Chemical Society (ACS). 2023.