DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting

Alexander Rodriguez, Anika Tabassum, Jiaming Cui, Jiajia Xie, Javen Ho, Pulak Agarwal, Bijaya Adhikari, B. Aditya Prakash. DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021. pages 15393-15400, AAAI Press, 2021. [doi]

@inproceedings{RodriguezTCXHAA21,
  title = {DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting},
  author = {Alexander Rodriguez and Anika Tabassum and Jiaming Cui and Jiajia Xie and Javen Ho and Pulak Agarwal and Bijaya Adhikari and B. Aditya Prakash},
  year = {2021},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/17808},
  researchr = {https://researchr.org/publication/RodriguezTCXHAA21},
  cites = {0},
  citedby = {0},
  pages = {15393-15400},
  booktitle = {Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021},
  publisher = {AAAI Press},
  isbn = {978-1-57735-866-4},
}