Eva L. Dyer - Google Scholar Citations

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	All	Since 2014
Citations	317	285
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Richard BaraniukVictor E. Cameron Professor, Electrical & Computer Engineering, Rice UniversityVerified email at rice.edu
Konrad Paul KordingUniversity Professor (PIK), bioengineering and neuroscience, UPennVerified email at upenn.edu
Doga GursoyArgonne National Laboratory; Northwestern UniversityVerified email at anl.gov
Aswin C SankaranarayananAssociate Professor, ECE, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Judy A PrasadUniversity of Chicago | Polsky Center for Entrepreneurship & InnovationVerified email at uchicago.edu
Farinaz KoushanfarProfessor and Henry Booker Faculty Scholar of ECE, UC San DiegoVerified email at ucsd.edu
Vincent De AndradeArgonne National LaboratoryVerified email at aps.anl.gov
Narayanan KasthuriUniversity of ChicagoVerified email at anl.gov
Mehrdad MajzoobiRice UniversityVerified email at rice.edu
Azalia MirhoseiniResearch Scientist, Google BrainVerified email at google.com
William R. Gray Roncal, Ph.D.Johns Hopkins University Applied Physics LaboratoryVerified email at jhu.edu
Tom GoldsteinAssistant Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Hugo FernandesSenior Data Scientist, Rockets of AwesomeVerified email at rocketsofawesome.com
Christoph StuderCornell University and Cornell Tech – VLSI Information Processing GroupVerified email at cornell.edu
Mohammad Gheshlaghi AzarResearch Scientist at DeepmindVerified email at google.com
Mark A. DavenportAssociate Professor of Electrical & Computer Engineering, Georgia Institute of TechnologyVerified email at gatech.edu
Lee E. MillerProfessor of Physiology, Physical Medicine and Rehabilitation, Biomedical Engineering, NorthwesternVerified email at northwestern.edu
Joshua T. VogelsteinDept of Biomedical Engineering, Johns Hopkins UniversityVerified email at jhu.edu

Eva L. Dyer

Assistant Professor at Georgia Institute of Technology

Verified email at gatech.edu - Homepage

Computational Neuroscience Machine Learning Signal Processing


Title	Cited by	Year
Greedy feature selection for subspace clustering EL Dyer, AC Sankaranarayanan, RG Baraniuk Journal of Machine Learning Research 14 (1), 2487-2517, 2013	139	2013
Rapid FPGA characterzation using clock synthesis and signal sparsity M Majzoobi, E Dyer, A Elnably, F Koushanfar IEEE International Test Conference (ITC), Austin, TX, 2010	29*	2010
Quantifying mesoscale neuroanatomy using x-ray microtomography EL Dyer, WG Roncal, JA Prasad, HL Fernandes, D Gürsoy, V De Andrade, ... eneuro 4 (5), 2017	21*	2017
Low-dose x-ray tomography through a deep convolutional neural network X Yang, V De Andrade, W Scullin, EL Dyer, N Kasthuri, F De Carlo, ... Scientific reports 8 (1), 2575, 2018	15	2018
Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition R Patel, T Goldstein, E Dyer, A Mirhoseini, R Baraniuk Proceedings of the 2016 SIAM International Conference on Data Mining, 594-602, 2016	14*	2016
Self-expressive decompositions for matrix approximation and clustering EL Dyer, TA Goldstein, R Patel, KP Kording, RG Baraniuk arXiv preprint arXiv:1505.00824, 2015	14	2015
RankMap: A Framework for Distributed Learning From Dense Data Sets A Mirhoseini, EL Dyer, EM Songhori, R Baraniuk, F Koushanfar IEEE transactions on neural networks and learning systems 29 (7), 2717-2730, 2017	11*	2017
A robust and efficient method to recover neural events from noisy and corrupted data EL Dyer, C Studer, JT Robinson, RG Baraniuk 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 593-596, 2013	11	2013
Validation system of MR image overlay and other needle insertion techniques JD Westwood Medicine Meets Virtual Reality 15: In Vivo, in Vitro, in Silico: Designing …, 2007	11*	2007
Recovering spikes from noisy neuronal calcium signals via structured sparse approximation EL Dyer, MF Duarte, DH Johnson, RG Baraniuk International Conference on Latent Variable Analysis and Signal Separation …, 2010	9	2010
Latent factors and dynamics in motor cortex and their application to brain–machine interfaces C Pandarinath, KC Ames, AA Russo, A Farshchian, LE Miller, EL Dyer, ... Journal of Neuroscience 38 (44), 9390-9401, 2018	8	2018
Approximating cellular densities from high-resolution neuroanatomical imaging data TJ LaGrow, MG Moore, JA Prasad, MA Davenport, EL Dyer 2018 40th Annual International Conference of the IEEE Engineering in …, 2018	6	2018
Subspace clustering with dense representations EL Dyer, C Studer, RG Baraniuk 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013	6	2013
A cryptography-based approach for movement decoding EL Dyer, MG Azar, MG Perich, HL Fernandes, S Naufel, LE Miller, ... Nature biomedical engineering 1 (12), 967, 2017	5	2017
An automated pipeline for the collection, transfer, and processing of large-scale tomography data M Du, R Vescovi, R Chard, N Kasthuri, C Jacobsen, E Dyer, D Gürsoy Optics and the Brain, BF4C. 2, 2018	3	2018
Endogenous sparse recovery EL Dyer Rice University, 2012	3	2012
Hybrid modeling of non-stationary process variations E Dyer, M Majzoobi, F Koushanfar Proceedings of the 48th Design Automation Conference, 194-199, 2011	3	2011
Generative models and abstractions for large-scale neuroanatomy datasets D Rolnick, EL Dyer Current opinion in neurobiology 55, 112-120, 2019	2	2019
Convex relaxation regression: Black-box optimization of smooth functions by learning their convex envelopes MG Azar, E Dyer, K Kording arXiv preprint arXiv:1602.02191, 2016	2	2016
Learning hybrid linear models via sparse recovery EL Dyer, AC Sankaranarayanan, RG Baraniuk SPARS 2011 Proceedings, 2011	2	2011

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