DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks - a Case Study For Covid-19 Spread and Interventions - researchr publication authors

researchr

You are not signed in
Sign in
Sign up

Ayush Chopra, Ramesh Raskar, Jayakumar Subramanian, Balaji Krishnamurthy, Esma Senturk Gel, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley. DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks - a Case Study For Covid-19 Spread and Interventions. In Winter Simulation Conference, WSC 2021, Phoenix, AZ, USA, December 12-15, 2021. pages 1-12, IEEE, 2021. [doi]

This author has not been identified. Look up 'Ayush Chopra' in GoogleThis author has not been identified. Look up 'Ramesh Raskar' in GoogleThis author has not been identified. Look up 'Jayakumar Subramanian' in GoogleThis author has not been identified. Look up 'Balaji Krishnamurthy' in GoogleThis author has not been identified. Look up 'Esma Senturk Gel' in GoogleThis author has not been identified. Look up 'Santiago Romero-Brufau' in GoogleThis author has not been identified. Look up 'Kalyan S. Pasupathy' in GoogleThis author has not been identified. Look up 'Thomas C. Kingsley' in Google

runs on WebDSL