Sang-Yun Oh
Title
Cited by
Cited by
Year
MAXIMA-1: a measurement of the cosmic microwave background anisotropy on angular scales of 10'-5
S Hanany, P Ade, A Balbi, J Bock, J Borrill, A Boscaleri, P De Bernardis, ...
The Astrophysical Journal Letters 545 (1), L5, 2000
18212000
Cosmology from MAXIMA-1, BOOMERANG, and COBE DMR cosmic microwave background observations
AH Jaffe, PAR Ade, A Balbi, JJ Bock, JR Bond, J Borrill, A Boscaleri, ...
Physical Review Letters 86 (16), 3475, 2001
7782001
Copy number variants in schizophrenia: confirmation of five previous findings and new evidence for 3q29 microdeletions and VIPR2 duplications
DF Levinson, J Duan, S Oh, K Wang, AR Sanders, J Shi, N Zhang, ...
American Journal of Psychiatry 168 (3), 302-316, 2011
4432011
A convex pseudolikelihood framework for high dimensional partial correlation estimation with convergence guarantees
K Khare, SY Oh, B Rajaratnam
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2015
1062015
Making maps of the cosmic microwave background: The MAXIMA example
R Stompor, A Balbi, JD Borrill, PG Ferreira, S Hanany, AH Jaffe, AT Lee, ...
Physical Review D 65 (2), 022003, 2001
1022001
Genome-wide association study of multiplex schizophrenia pedigrees
DF Levinson, J Shi, K Wang, S Oh, B Riley, AE Pulver, DB Wildenauer, ...
American Journal of Psychiatry 169 (9), 963-973, 2012
632012
Communication-avoiding parallel sparse-dense matrix-matrix multiplication
P Koanantakool, A Azad, A Buluç, D Morozov, SY Oh, L Oliker, K Yelick
2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2016
372016
Asymmetric beams in cosmic microwave background anisotropy experiments
JHP Wu, A Balbi, J Borrill, PG Ferreira, S Hanany, AH Jaffe, AT Lee, S Oh, ...
The Astrophysical Journal Supplement Series 132 (1), 1, 2001
322001
Revealing fundamental physics from the Daya Bay Neutrino Experiment using deep neural networks
E Racah, S Ko, P Sadowski, W Bhimji, C Tull, SY Oh, P Baldi
2016 15th IEEE International Conference on Machine Learning and Applications …, 2016
302016
Optimization methods for sparse pseudo-likelihood graphical model selection
S Oh, O Dalal, K Khare, B Rajaratnam
Advances in Neural Information Processing Systems 27, 667-675, 2014
282014
Generalized pseudolikelihood methods for inverse covariance estimation
A Ali, K Khare, SY Oh, B Rajaratnam
Artificial Intelligence and Statistics, 280-288, 2017
172017
Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation
P Koanantakool, A Ali, A Azad, A Buluc, D Morozov, L Oliker, K Yelick, ...
International Conference on Artificial Intelligence and Statistics, 1376-1386, 2018
152018
Improved quantitation of dynamic SPECT via fully 4-D joint estimation of compartmental models and blood input function directly from projections
BW Reutter, S Oh, GT Gullberg, RH Huesman
IEEE Nuclear Science Symposium Conference Record, 2005 4, 2337-2341, 2005
152005
Methods, systems, and apparatus to design online advertising units via a web-based application
PHI Kim, H Lee, J Park, SY Oh
US Patent 9,202,231, 2015
102015
Schizophrenia Psychiatric GWAS Consortium: Genome-wide association study of multiplex schizophrenia pedigrees
DF Levinson, J Shi, K Wang, S Oh, B Riley, AE Pulver, DB Wildenauer, ...
Am J Psychiatry 169 (9), 963-973, 2012
82012
A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data
K Khare, SY Oh, S Rahman, B Rajaratnam
Machine Learning 108 (12), 2061-2086, 2019
72019
Partial Separability and Functional Graphical Models for Multivariate Gaussian Processes
J Zapata, SY Oh, A Petersen
arXiv preprint arXiv:1910.03134, 2019
42019
Distributionally Robust Formulation and Model Selection for the Graphical Lasso
P Cisneros, A Petersen, SY Oh
International Conference on Artificial Intelligence and Statistics, 756-765, 2020
2020
Exploring Raw HEP Data using Deep Neural Networks at NERSC
W Bhimji, E Racah, S Ko, P Sadowski, C Tull, SY Oh, M Prabhat
Proceedings of the 38th International Conference on High Energy Physics …, 2016
2016
Deep Learning for Climate Pattern Detection
M Prabhat, Y Liu, J Correa, E Racah, SY Oh, A Khosrowshahi, DA Lavers, ...
AGU Fall Meeting Abstracts 2015, NH51F-1959, 2015
2015
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