Heman Shakeri | DeepAI

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Featured Co-authors

Tingting Zhang
11 publications
Philip E. Bourne
8 publications
Yaotian Wang
7 publications
Taylor R. Brown
6 publications
Michael J. Higgins
6 publications
Bruce A. Corliss
5 publications
Ali Tavasoli
3 publications
Ehsan Ardjmand
2 publications
Pietro Poggi-Corradini
2 publications
Teague Henry
2 publications
Mehrdad Fazli
2 publications

∙ 04/16/2023

Characterizing the load profile in power grids by Koopman mode decomposition of interconnected dynamics

Electricity load forecasting is crucial for effectively managing and opt...

0 Ali Tavasoli, et al. ∙

∙ 03/20/2023

MAD-FC: A Fold Change Visualization with Readability, Proportionality, and Symmetry

We propose a fold change visualization that demonstrates a combination o...

0 Bruce A. Corliss, et al. ∙

∙ 03/16/2023

Contra-Analysis for Determining Negligible Effect Size in Scientific Research

Scientific experiments study interventions that show evidence of an effe...

0 Bruce A. Corliss, et al. ∙

∙ 12/17/2022

Leveraging Wastewater Monitoring for COVID-19 Forecasting in the US: a Deep Learning study

The outburst of COVID-19 in late 2019 was the start of a health crisis t...

0 Mehrdad Fazli, et al. ∙

∙ 10/10/2022

Contra-Analysis: Prioritizing Meaningful Effect Size in Scientific Research

At every phase of scientific research, scientists must decide how to all...

0 Bruce A. Corliss, et al. ∙

∙ 05/24/2022

The Least Difference in Means: A Statistic for Effect Size Strength and Practical Significance

With limited resources, scientific inquiries must be prioritized for fur...

0 Bruce A. Corliss, et al. ∙

∙ 05/02/2022

Using Machine Learning to Evaluate Real Estate Prices Using Location Big Data

With everyone trying to enter the real estate market nowadays, knowing t...

0 Walter Coleman, et al. ∙

∙ 01/04/2022

The Most Difference in Means: A Statistic for Null and Near-Zero Results

Two-sample p-values test for statistical significance. Yet p-values cann...

0 Bruce A. Corliss, et al. ∙

∙ 08/01/2021

A purely data-driven framework for prediction, optimization, and control of networked processes: application to networked SIS epidemic model

Networks are landmarks of many complex phenomena where interweaving inte...

0 Ali Tavasoli, et al. ∙

∙ 08/29/2020

Maximizing the algebraic connectivity in multilayer networks with arbitrary interconnections

The second smallest eigenvalue of the Laplacian matrix is determinative ...

0 Ali Tavasoli, et al. ∙

∙ 10/02/2019

A new method for quantifying network cyclic structure to improve community detection

A distinguishing property of communities in networks is that cycles are ...

0 Behnaz Moradi-Jamei, et al. ∙

∙ 03/04/2019

Designing Optimal Multiplex Networks for Certain Laplacian Spectral Properties

We discuss the design of interlayer edges in a multiplex network, under ...

0 Heman Shakeri, et al. ∙

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