Benjamin Hurt

According to our database, Benjamin Hurt authored at least 6 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support.

Parantapa Bhattacharya, Jiangzhuo Chen, Stefan Hoops, Dustin Machi, Bryan L. Lewis, Srinivasan Venkatramanan, Mandy L. Wilson, Brian Klahn, Aniruddha Adiga, Benjamin Hurt, Joseph Outten, Abhijin Adiga, Andrew S. Warren, Young Yun Baek, Przemyslaw J. Porebski, Achla Marathe, Dawen Xie, Samarth Swarup, Anil Vullikanti, Henning S. Mortveit, Stephen G. Eubank, Christopher L. Barrett, Madhav Vinayak Marathe

Int. J. High Perform. Comput. Appl., 2023

A Multi-Team Multi-Model Collaborative Covid-19 Forecasting Hub for India.

Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Ambedkar Dukkipati, Tony Gracious, Shubham Gupta, Nihesh Rathod, Rajesh Sundaresan, Sarath Yasodharan, Kantha Rao Bhimala, Vidyadhar Mudkavi, Gopal Krishna Patra, Siva Athreya

Proceedings of the Winter Simulation Conference, 2023

Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts.

Aniruddha Adiga, Gursharn Kaur, Lijing Wang, Benjamin Hurt, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan L. Lewis, Madhav V. Marathe

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Enhancing COVID-19 Ensemble Forecasting Model Performance Using Auxiliary Data Sources.

Aniruddha Adiga, Gursharn Kaur, Benjamin Hurt, Lijing Wang, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan L. Lewis, Madhav V. Marathe

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Informing University Covid-19 Decisions Using Simple Compartmental Models.

Benjamin Hurt, Aniruddha Adiga, Madhav V. Marathe, Christopher L. Barrett

Proceedings of the Winter Simulation Conference, 2021

All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting.

Aniruddha Adiga, Lijing Wang, Benjamin Hurt, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan Leroy Lewis, Madhav V. Marathe

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021