@InProceedings{gao_et_al:LIPIcs.GIScience.2023.33, author = {Gao, Xiaowei and Haworth, James and Zhuang, Dingyi and Chen, Huanfa and Jiang, Xinke}, title = {{Uncertainty Quantification in the Road-Level Traffic Risk Prediction by Spatial-Temporal Zero-Inflated Negative Binomial Graph Neural Network(STZINB-GNN)}}, booktitle = {12th International Conference on Geographic Information Science (GIScience 2023)}, pages = {33:1--33:6}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-288-4}, ISSN = {1868-8969}, year = {2023}, volume = {277}, editor = {Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.33}, URN = {urn:nbn:de:0030-drops-189286}, doi = {10.4230/LIPIcs.GIScience.2023.33}, annote = {Keywords: Traffic Risk Prediction, Uncertainty Quantification, Zero-Inflated Issues, Road Safety} }