Kayhan Batmanghelich
Title
Cited by
Cited by
Year
Prediction of MCI to AD conversion, via MRI, CSF biomarkers, and pattern classification
C Davatzikos, P Bhatt, LM Shaw, KN Batmanghelich, JQ Trojanowski
Neurobiology of aging 32 (12), 2322. e19-2322. e27, 2011
5052011
Deep ordinal regression network for monocular depth estimation
H Fu, M Gong, C Wang, K Batmanghelich, D Tao
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
4812018
Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline
Y Fan, N Batmanghelich, CM Clark, C Davatzikos, ...
Neuroimage 39 (4), 1731-1743, 2008
4772008
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
3972018
Information processing in medical imaging
CN De Graaff, MA Viergever
Springer Science & Business Media, 2013
1092013
Nonparametric Spherical Topic Modeling with Word Embeddings
S Batmanghelich, Kayhan and Saeedi, Ardavan and Narasimhan, Karthik and Gershman
arXiv preprint arXiv:1604.00126, 2016
72*2016
Generative-discriminative basis learning for medical imaging
NK Batmanghelich, B Taskar, C Davatzikos
IEEE transactions on medical imaging 31 (1), 51-69, 2011
662011
Joint modeling of imaging and genetics
NK Batmanghelich, AV Dalca, MR Sabuncu, P Golland
International Conference on Information Processing in Medical Imaging, 766-777, 2013
332013
A general and unifying framework for feature construction, in image-based pattern classification
N Batmanghelich, B Taskar, C Davatzikos
International Conference on Information Processing in Medical Imaging, 423-434, 2009
322009
Geometry-consistent generative adversarial networks for one-sided unsupervised domain mapping
H Fu, M Gong, C Wang, K Batmanghelich, K Zhang, D Tao
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
302019
Disease classification and prediction via semi-supervised dimensionality reduction
KN Batmanghelich, HY Dong, KM Pohl, B Taskar, C Davatzikos
2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro …, 2011
262011
Transfer learning with label noise
X Yu, T Liu, M Gong, K Zhang, K Batmanghelich, D Tao
arXiv preprint arXiv:1707.09724, 2017
232017
An efficient and provable approach for mixture proportion estimation using linear independence assumption
X Yu, T Liu, M Gong, K Batmanghelich, D Tao
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
202018
Causal discovery in the presence of measurement error: Identifiability conditions
K Zhang, M Gong, J Ramsey, K Batmanghelich, P Spirtes, C Glymour
arXiv preprint arXiv:1706.03768, 2017
192017
Unsupervised discovery of emphysema subtypes in a large clinical cohort
P Binder, NK Batmanghelich, RSJ Estepar, P Golland
International Workshop on Machine Learning in Medical Imaging, 180-187, 2016
192016
Probabilistic modeling of imaging, genetics and diagnosis
NK Batmanghelich, A Dalca, G Quon, M Sabuncu, P Golland
IEEE transactions on medical imaging 35 (7), 1765-1779, 2016
192016
Diversifying sparsity using variational determinantal point processes
NK Batmanghelich, G Quon, A Kulesza, M Kellis, P Golland, L Bornn
arXiv preprint arXiv:1411.6307, 2014
182014
Twin Auxiliary Classifiers GAN
M Gong, Y Xu, C Li, K Zhang, K Batmanghelich
NeurIPs preprint arXiv:1907.02690, 2019
172019
Weakly supervised disentanglement by pairwise similarities
J Chen, K Batmanghelich
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3495-3502, 2020
142020
Causal generative domain adaptation networks
M Gong, K Zhang, B Huang, C Glymour, D Tao, K Batmanghelich
arXiv preprint arXiv:1804.04333, 2018
132018
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Articles 1–20