Spatial Probabilistic Forecasting
Spatial Probabilistic Forecasting is a probabilistic forecasting methodology that quantifies uncertainty in predictions across spatial domains by modeling the joint probability distribution of outcomes at multiple geographic locations.
38
Publications
1.7K
Citations
107
Authors
54
Institutions
Publications per year
2017–2026
14
Parents
38
DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models
Haomin Wen, Youfang Lin, Yutong Xia et al. · 2023 · 92 citations · Full text
Computing, Data Science, Forecasting +16
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54
University of Washington
Seattle, United States
3 h-index
4 publications
372 citations
Texas A&M University
College Station, United States
3 h-index
6 publications
156 citations
Duke University
Durham, United States
2 h-index
2 publications
150 citations
Technical University of Denmark
Kongens Lyngby, Denmark
2 h-index
8 publications
564 citations

UNSW Sydney
Sydney, Australia
2 h-index
4 publications
100 citations

University of Manitoba
Winnipeg, Canada
2 h-index
2 publications
50 citations
Jilin University
Changchun, China
2 h-index
6 publications
108 citations

Oklahoma State University
Stillwater, United States
2 h-index
2 publications
52 citations
1–8 of 54
1 publications · 42 citations
2
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2 publications · 67 citations
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TSTE · 1 publications · 44 citations
2
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1 publications · 27 citations
1
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1 publications · 47 citations
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