Eva L. Dyer
Cited by
Cited by
Greedy feature selection for subspace clustering
EL Dyer, AC Sankaranarayanan, RG Baraniuk
Journal of Machine Learning Research 14 (1), 2487-2517, 2013
Quantifying mesoscale neuroanatomy using X-ray microtomography
EL Dyer, WG Roncal, JA Prasad, HL Fernandes, D Gürsoy, V De Andrade, ...
Eneuro 4 (5), 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), 1-13, 2018
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
Rapid FPGA characterization using clock synthesis and signal sparsity
M Majzoobi, E Dyer, A Elnably, F Koushanfar
IEEE International Test Conference (ITC), Austin, TX, 2010
A cryptography-based approach for movement decoding
EL Dyer, MG Azar, MG Perich, HL Fernandes, S Naufel, LE Miller, ...
Nature biomedical engineering 1 (12), 967-976, 2017
Hierarchical optimal transport for multimodal distribution alignment
J Lee, M Dabagia, EL Dyer, CJ Rozell
arXiv preprint arXiv:1906.11768, 2019
Self-expressive decompositions for matrix approximation and clustering
EL Dyer, TA Goldstein, R Patel, KP Kording, RG Baraniuk
arXiv preprint arXiv:1505.00824, 2015
Bootstrapped representation learning on graphs
S Thakoor, C Tallec, MG Azar, M Azabou, EL Dyer, R Munos, P Veličković, ...
arXiv preprint arXiv:2102.06514, 2021
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
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
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
Pyglmnet: Python implementation of elastic-net regularized generalized linear models
M Jas, T Achakulvisut, A Idrizović, D Acuna, M Antalek, V Marques, ...
Journal of Open Source Software 5 (47), 2020
Subspace clustering with dense representations
EL Dyer, C Studer, RG Baraniuk
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
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
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
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
A three-dimensional thalamocortical dataset for characterizing brain heterogeneity
JA Prasad, AH Balwani, EC Johnson, JD Miano, V Sampathkumar, ...
Scientific Data 7 (1), 1-7, 2020
Generative models and abstractions for large-scale neuroanatomy datasets
D Rolnick, EL Dyer
Current opinion in neurobiology 55, 112-120, 2019
Mine your own view: Self-supervised learning through across-sample prediction
M Azabou, MG Azar, R Liu, CH Lin, EC Johnson, K Bhaskaran-Nair, ...
arXiv preprint arXiv:2102.10106, 2021
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