R
Rogers F. Silva
Researcher at Georgia Institute of Technology
Publications - 49
Citations - 1808
Rogers F. Silva is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Independent component analysis & Infomax. The author has an hindex of 14, co-authored 43 publications receiving 1459 citations. Previous affiliations of Rogers F. Silva include University of New Mexico & The Mind Research Network.
Papers
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Journal ArticleDOI
A Baseline for the Multivariate Comparison of Resting-State Networks
Elena A. Allen,Erik B. Erhardt,Eswar Damaraju,William Gruner,William Gruner,Judith M. Segall,Judith M. Segall,Rogers F. Silva,Rogers F. Silva,Martin Havlicek,Martin Havlicek,Srinivas Rachakonda,Jill Fries,Ravi Kalyanam,Ravi Kalyanam,Andrew M. Michael,Arvind Caprihan,Jessica A. Turner,Jessica A. Turner,Tom Eichele,Steven Adelsheim,Angela D. Bryan,Angela D. Bryan,Juan R. Bustillo,Vincent P. Clark,Vincent P. Clark,Sarah W. Feldstein Ewing,Francesca M. Filbey,Francesca M. Filbey,Corey C. Ford,Kent E. Hutchison,Kent E. Hutchison,Rex E. Jung,Rex E. Jung,Kent A. Kiehl,Kent A. Kiehl,Piyadasa W. Kodituwakku,Yuko M. Komesu,Andrew R. Mayer,Andrew R. Mayer,Godfrey D. Pearlson,John P. Phillips,John P. Phillips,Joseph Sadek,Michael Stevens,Ursina Teuscher,Ursina Teuscher,Robert J. Thoma,Vince D. Calhoun +48 more
TL;DR: A multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing is introduced and is demonstrated by identifying the effects of age and gender on the resting-state networks of 603 healthy adolescents and adults.
Journal ArticleDOI
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
Anees Abrol,Zening Fu,Mustafa Salman,Rogers F. Silva,Yuhui Du,Yuhui Du,Sergey M. Plis,Vince D. Calhoun +7 more
TL;DR: In this article, the authors conduct a large-scale systematic comparison profiled in multiple classification and regression tasks on structural MRI images and show the importance of representation learning for deep learning for brain imaging data analysis.
Journal ArticleDOI
Independent Component Analysis for Brain fMRI Does Indeed Select for Maximal Independence
Vince D. Calhoun,Vince D. Calhoun,Vamsi K. Potluru,Vamsi K. Potluru,Ronald Phlypo,Rogers F. Silva,Rogers F. Silva,Barak A. Pearlmutter,Arvind Caprihan,Sergey M. Plis,Tulay Adali +10 more
TL;DR: It is shown that these experiments fall short of proving claims that two independent component analysis algorithms, Infomax and FastICA, select for sparsity rather than independence, and that the ICA algorithms are indeed doing what they are designed to do: identify maximally independent sources.
Proceedings ArticleDOI
The tenth annual mlsp competition: schizophrenia classification challenge
Rogers F. Silva,Eduardo Castro,Cota Navin Gupta,Mustafa S. Çetin,Mohammad R. Arbabshirani,Vamsi K. Potluru,Sergey M. Plis,Vince D. Calhoun +7 more
TL;DR: Details about the competition setup, the winning strategies, and basic analyses of the submitted entries are reviewed to provide basic analyses and a discussion of the advances made to the neuroimaging and machine learning fields are discussed.
Journal ArticleDOI
Correction: Independent Component Analysis for Brain fMRI Does Indeed Select for Maximal Independence
Vince D. Calhoun,Vamsi K. Potluru,Ronald Phlypo,Rogers F. Silva,Barak A. Pearlmutter,Arvind Caprihan,Sergey M. Plis,Tulay Adali +7 more
TL;DR: This article was republished on October 23, 2013 because of missing equations.