Dataset Groups Activity Stream PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation Spatiotemporal imputation aims to fill the missing values according to the observed values and the underlying spatiotemporal dependence of them. BibTex: @dataset{Mingzhe_Liu_and_Han_Huang_and_Hao_Feng_and_Leilei_Sun_and_Bowen_Du_and_Yanjie_Fu_2024, abstract = {Spatiotemporal imputation aims to fill the missing values according to the observed values and the underlying spatiotemporal dependence of them.}, author = {Mingzhe Liu and Han Huang and Hao Feng and Leilei Sun and Bowen Du and Yanjie Fu}, doi = {10.57702/3782dgb9}, institution = {No Organization}, keyword = {'diffusion model', 'spatiotemporal dependency learning', 'spatiotemporal imputation'}, month = {dec}, publisher = {TIB}, title = {PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation}, url = {https://service.tib.eu/ldmservice/dataset/pristi--a-conditional-diffusion-framework-for-spatiotemporal-imputation}, year = {2024} }
