Segovia Dominguez, I.J., Lee, H., Zhen, Z., Wagh, R., and Gel, Y.R. TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions. Retrieved from https://par.nsf.gov/biblio/10284521. Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) . Web. doi:10.1007/978-3-030-75762-5_17.

Segovia Dominguez, I.J., Lee, H., Zhen, Z., Wagh, R., & Gel, Y.R. TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions. Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), (). Retrieved from https://par.nsf.gov/biblio/10284521. https://doi.org/10.1007/978-3-030-75762-5_17

Segovia Dominguez, I.J., Lee, H., Zhen, Z., Wagh, R., and Gel, Y.R. "TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions". Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) (). Country unknown/Code not available. https://doi.org/10.1007/978-3-030-75762-5_17. https://par.nsf.gov/biblio/10284521.

@article{osti_10284521,
place = {Country unknown/Code not available}, title = {TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions}, url = {https://par.nsf.gov/biblio/10284521}, DOI = {10.1007/978-3-030-75762-5_17}, abstractNote = {}, journal = {Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)}, author = {Segovia Dominguez, I.J. and Lee, H. and Zhen, Z. and Wagh, R. and Gel, Y.R.}, }