Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting is a research paper (2020). On theSindex it has a DataRank of 0.483. It has been cited 24 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
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Base Score Contribution
0.483
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →National Institutes of Health
Grant: 3R01GM109718-05S1
Systems Analysis of Social Pathways of Epidemics to Reduce Health Disparities
National Science Foundation
Grant: 1917819
Expeditions: Collaborative Research: Global Pervasive Computational Epidemiology
National Science Foundation
Grant: 1916805
Collaborative Research: Framework: Software: CINES: A Scalable Cyberinfrastructure for Sustained Innovation in Network Engineering and Science
National Science Foundation
Grant: 2027541
RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks
National Science Foundation
Grant: 2028004
RAPID: Collaborative: Transfer Learning Techniques for Better Response to COVID-19 in the US
National Science Foundation
Grant: 1918656
Expeditions: Collaborative Research: Global Pervasive Computational Epidemiology
FWCI
5.54
Citation Percentile
1.0%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals