Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting

no code implementations • 27 Oct 2020 • Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, Jiangzhuo Chen, Bryan Lewis, Madhav Marathe

Deep learning-based time series models for forecasting have recently gained popularity and have been successfully used for epidemic forecasting.

Clustering Spatio-Temporal Forecasting +2

Models for COVID-19 Pandemic: A Comparative Analysis

no code implementations • 21 Sep 2020 • Aniruddha Adiga, Devdatt Dubhashi, Bryan Lewis, Madhav Marathe, Srinivasan Venkatramanan, Anil Vullikanti

COVID-19 pandemic represents an unprecedented global health crisis in the last 100 years.

Efficient Thresholded Correlation using Truncated Singular Value Decomposition

1 code implementation • 22 Dec 2015 • James Baglama, Michael Kane, Bryan Lewis, Alex Poliakov

Efficiently computing a subset of a correlation matrix consisting of values above a specified threshold is important to many practical applications.

Computation

Scatter Matrix Concordance: A Diagnostic for Regressions on Subsets of Data

no code implementations • 12 Jul 2015 • Michael J. Kane, Bryan Lewis, Sekhar Tatikonda, Simon Urbanek

Linear regression models depend directly on the design matrix and its properties.

Computational Efficiency regression