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Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway
The Mumbai Suburban Railways, locals, are a key transit infrastructure o...
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Pandemic Informatics: Preparation, Robustness, and Resilience
Infectious diseases cause more than 13 million deaths a year, worldwide....
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Wisdom of the Ensemble: Improving Consistency of Deep Learning Models
Deep learning classifiers are assisting humans in making decisions and h...
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Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting
The COVID-19 pandemic represents the most significant public health disa...
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SubGraph2Vec: Highly-Vectorized Tree-likeSubgraph Counting
Subgraph counting aims to count occurrences of a template T in a given n...
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Models for COVID-19 Pandemic: A Comparative Analysis
COVID-19 pandemic represents an unprecedented global health crisis in th...
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A GraphBLAS Approach for Subgraph Counting
Subgraph counting aims to count the occurrences of a subgraph template T...
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Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation
The convergence of HPC and data-intensive methodologies provide a promis...
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High-Performance Massive Subgraph Counting using Pipelined Adaptive-Group Communication
Subgraph counting aims to count the number of occurrences of a subgraph ...
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Calibrating a Stochastic Agent Based Model Using Quantile-based Emulation
In a number of cases, the Quantile Gaussian Process (QGP) has proven eff...
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