Joint Spatial-Temporal Models is a statistical modeling framework in Bayesian disease mapping that simultaneously accounts for spatial and temporal dependencies in disease incidence or prevalence data to improve inference on geographic and temporal patterns of risk.
140
Publications
7.9K
Citations
538
Authors
309
Institutions
Publications per year
2017–2026
79
Parents
Publications
140
Bayesian Modelling of Inseparable SpaceTime Variation in Disease Risk
2014 · 536 citations
Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification
Shuangjie Xu, Yu Cheng, Kang Gu et al. · 2017 · 342 citations
1–5 of 140
Authors
538
- CB
3
h-index
- MD
3
h-index
- AL
3
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- AB
3
h-index
- TG
3
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1–5 of 538
Institutions
309
Imperial College London
London, United Kingdom
7 h-index
19 publications
1.2K citations
Medical University of South Carolina
Charleston, United States
4 h-index
10 publications
207 citations
Universidad Pública de Navarra (UPNA)
Pamplona, Spain
4 h-index
18 publications
623 citations
University of Glasgow
Glasgow, United Kingdom
3 h-index
5 publications
184 citations
University of Southampton
Southampton, United Kingdom
3 h-index
8 publications
582 citations
University of Florida
Gainesville, United States
3 h-index
7 publications
177 citations
Southeast University
Nanjing, China
3 h-index
7 publications
454 citations
National Yang Ming Chiao Tung University
Hsinchu, Taiwan
3 h-index
5 publications
146 citations
1–8 of 309
Venues
- Statistics in Medicine
11 publications · 1.1K citations
11
h-index
- Spatial Statistics
6 publications · 267 citations
6
h-index
- PLoS ONE
6 publications · 165 citations
5
h-index
- Journal of the Royal Statistical Society Series A (Statistics in Society)
4 publications · 216 citations
4
h-index
- Spatial and Spatio-temporal Epidemiology
4 publications · 98 citations
4
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1–5