Gregery T Buzzard

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Charles A BoumanProfessor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
Ann RundellAssociate Professor of Biomedical Engineering, Purdue UniversityVerified email at purdue.edu
Ankush ChakrabartyPrincipal Research Scientist at Mitsubishi Electric Research Laboratories (MERL)Verified email at merl.com
Stanislaw H. ŻakProfessor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
Dong Hye YeAssistant Professor, Georgia State UniversityVerified email at gsu.edu
Singanallur V. VenkatakrishnanResearch Staff - Imaging, Signals and Machine Learning, Oak Ridge National LaboratoryVerified email at ornl.gov
Dilshan GodaliyaddaSamsung Research AmericaVerified email at samsung.com
Brendt WohlbergLos Alamos National LaboratoryVerified email at lanl.gov
Martin CorlessAeronautics & Astronautics, Purdue UniversityVerified email at purdue.edu
Bradley J. LucierProfessor Emeritus of Mathematics and Computer Science, Purdue UniversityVerified email at math.purdue.edu
Vu DinhUniversity of DelawareVerified email at udel.edu
Dor Ben-AmotzPurdue UniversityVerified email at purdue.edu
Suhas SreehariStaff Research Scientist at Oak Ridge National LabVerified email at ornl.gov
Jason BazilAssistant Professor, Michigan State UniversityVerified email at msu.edu
Lawrence DrummyAir Force Research LaboratoryVerified email at us.af.mil
Michael GroeberThe Ohio State UniversityVerified email at osu.edu
Jeff FoxDirector, Research Development, University of VirginiaVerified email at virginia.edu
Ping WangProfessor, Huazhong University of Science and technology (HUST)Verified email at hust.edu.cn
David M UmulisProfessor and Associate Head for Research; Purdue UniversityVerified email at purdue.edu
Jeff SimmonsAir Force Research LaboratoryVerified email at us.af.mil

Gregery T Buzzard

Professor of Mathematics, Purdue University

Verified email at purdue.edu - Homepage

Uncertainty quantification experiment design signal and image estimation


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Plug-and-play priors for bright field electron tomography and sparse interpolation S Sreehari, SV Venkatakrishnan, B Wohlberg, GT Buzzard, LF Drummy, ... IEEE Transactions on Computational Imaging 2 (4), 408-423, 2016	298	2016
Plug-and-play unplugged: Optimization-free reconstruction using consensus equilibrium GT Buzzard, SH Chan, S Sreehari, CA Bouman SIAM Journal on Imaging Sciences 11 (3), 2001-2020, 2018	138	2018
Plug-and-play methods for magnetic resonance imaging: Using denoisers for image recovery R Ahmad, CA Bouman, GT Buzzard, S Chan, S Liu, ET Reehorst, ... IEEE signal processing magazine 37 (1), 105-116, 2020	118	2020
State and unknown input observers for nonlinear systems with bounded exogenous inputs A Chakrabarty, MJ Corless, GT Buzzard, SH Żak, AE Rundell IEEE Transactions on Automatic Control 62 (11), 5497-5510, 2017	87	2017
Global sensitivity analysis using sparse grid interpolation and polynomial chaos GT Buzzard Reliability Engineering & System Safety 107, 82-89, 2012	80	2012
Support vector machine informed explicit nonlinear model predictive control using low-discrepancy sequences A Chakrabarty, V Dinh, MJ Corless, AE Rundell, SH Żak, GT Buzzard IEEE Transactions on Automatic Control 62 (1), 135-148, 2016	75	2016
Modeling mitochondrial bioenergetics with integrated volume dynamics JN Bazil, GT Buzzard, AE Rundell PLoS computational biology 6 (1), e1000632, 2010	74	2010
Infinitely many periodic attractors for holomorphic maps of 2 variables GT Buzzard Annals of mathematics 145 (2), 389-417, 1997	66	1997
Variance-based global sensitivity analysis via sparse-grid interpolation and cubature GT Buzzard, D Xiu Communications in Computational Physics 9 (3), 542-567, 2011	65	2011
Algebraic surfaces holomorphically dominable by C^ 2 GT Buzzard, S Lu arXiv preprint math/9903193, 1999	57	1999
Photon level chemical classification using digital compressive detection DS Wilcox, GT Buzzard, BJ Lucier, P Wang, D Ben-Amotz Analytica chimica acta 755, 17-27, 2012	48	2012
Digital compressive chemical quantitation and hyperspectral imaging DS Wilcox, GT Buzzard, BJ Lucier, OG Rehrauer, P Wang, D Ben-Amotz Analyst 138 (17), 4982-4990, 2013	40	2013
Model‐based design of experiments for cellular processes A Chakrabarty, GT Buzzard, AE Rundell Wiley Interdisciplinary Reviews: Systems Biology and Medicine 5 (2), 181-203, 2013	38	2013
An embedding of {\bf C} in {\bf C} with hyperbolic complement GT Buzzard, JE Fornæss arXiv preprint math/9506211, 1995	38	1995
An embedding of {\bf C} in {\bf C} with hyperbolic complement GT Buzzard, JE Fornæss arXiv preprint math/9506211, 1995	38	1995
Deep back projection for sparse-view CT reconstruction DH Ye, GT Buzzard, M Ruby, CA Bouman 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018	36	2018
A framework for dynamic image sampling based on supervised learning GMDP Godaliyadda, DH Ye, MD Uchic, MA Groeber, GT Buzzard, ... IEEE Transactions on Computational Imaging 4 (1), 1-16, 2017	36*	2017
A supervised learning approach for dynamic sampling GM Godaliyadda, DH Ye, MD Uchic, MA Groeber, GT Buzzard, ... Electronic Imaging 2016 (19), 1-8, 2016	36	2016
A global parallel model based design of experiments method to minimize model output uncertainty JN Bazil, GT Buzzard, AE Rundell Bulletin of mathematical biology 74, 688-716, 2012	31	2012
State and unknown input observers for nonlinear systems with delayed measurements A Chakrabarty, E Fridman, SH Żak, GT Buzzard Automatica 95, 246-253, 2018	30	2018

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