On the data-driven inference of modulatory networks in climate science: an application to West African rainfall
Diego Luis Gonzalez(Oak Ridge National Laboratory), Nagiza F. Samatova(North Carolina State University), Saurabh V. Pendse(North Carolina State University), Gonzalo A. Bello(Oak Ridge National Laboratory), Isaac K. Tetteh(University of Health and Allied Sciences), Yu Jian(North Carolina State University), F.H.M. Semazzi(North Carolina State University), S. Srinivas(Oak Ridge National Laboratory), Michael Angus(North Carolina State University), Vijay Kumar(National Institute of Technology Hamirpur), K. A. Padmanabhan(Oak Ridge National Laboratory)
Cited by 3
Related Papers
Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data
|IEEE Transactions on Knowledge and Data Engineering|2017|1.5k
Anomaly detection in dynamic networks: a survey
|Wiley Interdisciplinary Reviews Computational Statistics|2015|376
Differential impacts of rainfall and irrigation on agricultural production in Nigeria: Any lessons for climate-smart agriculture?
|Agricultural Water Management|2016|140
Chitosan and chitosan derivatives: Recent advancements in production and applications in environmental remediation
|Environmental Advances|2023|81