6 citations · 14 across the 6 of their papers we have counts for
8 papers
Accurately Estimating Unreported Infections using Information Theory
Jiaming Cui, Bijaya Adhikari, Arash Haddadan +4
One of the most significant challenges in combating against the spread of infectious diseases was the difficulty in estimating the true magnitude of infections. Unreported infectio…
EINNs: Epidemiologically-informed Neural Networks
Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan +2
We introduce EINNs, a framework crafted for epidemic forecasting that builds upon the theoretical grounds provided by mechanistic models as well as the data-driven expressibility a…
Modeling and Evaluation of Clustering Patient Care into Bubbles
D. M. Hasibul Hasan, Alex Rohwer, Hankyu Jang +5
COVID-19 has caused an enormous burden on healthcare facilities around the world. Cohorting patients and healthcare professionals (HCPs) into "bubbles" has been proposed as an infe…
Incorporating Expert Guidance in Epidemic Forecasting
Alexander Rodríguez, Bijaya Adhikari, Naren Ramakrishnan +1
Forecasting influenza like illnesses (ILI) has rapidly progressed in recent years from an art to a science with a plethora of data-driven methods. While these methods have achieved…
Mapping Network States Using Connectivity Queries
Alexander Rodríguez, Bijaya Adhikari, Andrés D. González +3
Can we infer all the failed components of an infrastructure network, given a sample of reachable nodes from supply nodes? One of the most critical post-disruption processes after a…
NetReAct: Interactive Learning for Network Summarization
Sorour E. Amiri, Bijaya Adhikari, John Wenskovitch +4
Generating useful network summaries is a challenging and important problem with several applications like sensemaking, visualization, and compression. However, most of the current…
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19
Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari +3
Forecasting influenza in a timely manner aids health organizations and policymakers in adequate preparation and decision making. However, effective influenza forecasting still rema…
Distributed Representation of Subgraphs
Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan +1
Network embeddings have become very popular in learning effective feature representations of networks. Motivated by the recent successes of embeddings in natural language processin…