APA (7th ed.) Citation

Barhoumi, K., Iyer, T., Li, J., & Mo Choi, S. (2022). Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa. International Monetary Fund.

Chicago Style (17th ed.) Citation

Barhoumi, Karim, Tara Iyer, Jiakun Li, and Seung Mo Choi. Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa. Washington, D.C.: International Monetary Fund, 2022.

MLA (8th ed.) Citation

Barhoumi, Karim, et al. Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa. International Monetary Fund, 2022.