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 | 1884 | 2018 |
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 | 1859 | 2018 |
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 | 652 | 2011 |
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 | 581 | 2008 |
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 | 219 | 2019 |
Nonparametric Spherical Topic Modeling with Word Embeddings S Batmanghelich, Kayhan and Saeedi, Ardavan and Narasimhan, Karthik and Gershman arXiv preprint arXiv:1604.00126, 2016 | 121* | 2016 |
Can contrastive learning avoid shortcut solutions? J Robinson, L Sun, K Yu, K Batmanghelich, S Jegelka, S Sra Advances in neural information processing systems 34, 4974-4986, 2021 | 112 | 2021 |
Explanation by Progressive Exaggeration S Singla, B Pollack, J Chen, K Batmanghelich International Conference on Learning Representations, 2019 | 110 | 2019 |
Twin Auxiliary Classifiers GAN M Gong, Y Xu, C Li, K Zhang, K Batmanghelich NeurIPs preprint arXiv:1907.02690, 2019 | 90 | 2019 |
Generative-discriminative basis learning for medical imaging NK Batmanghelich, B Taskar, C Davatzikos IEEE transactions on medical imaging 31 (1), 51-69, 2011 | 88 | 2011 |
Weakly supervised disentanglement by pairwise similarities J Chen, K Batmanghelich Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3495-3502, 2020 | 61 | 2020 |
CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation R Dorent, A Kujawa, M Ivory, S Bakas, N Rieke, S Joutard, B Glocker, ... Medical Image Analysis 83, 102628, 2023 | 60 | 2023 |
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 | 53 | 2018 |
Hierarchical amortized GAN for 3D high resolution medical image synthesis L Sun, J Chen, Y Xu, M Gong, K Yu, K Batmanghelich IEEE journal of biomedical and health informatics 26 (8), 3966-3975, 2022 | 52 | 2022 |
Explaining the black-box smoothly—a counterfactual approach S Singla, M Eslami, B Pollack, S Wallace, K Batmanghelich Medical image analysis 84, 102721, 2023 | 50 | 2023 |
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 | 44 | 2011 |
Joint modeling of imaging and genetics NK Batmanghelich, AV Dalca, MR Sabuncu, P Golland Information Processing in Medical Imaging: 23rd International Conference …, 2013 | 43 | 2013 |
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 | 40 | 2017 |
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 | 38 | 2016 |
Transfer learning with label noise X Yu, T Liu, M Gong, K Zhang, K Batmanghelich, D Tao arXiv preprint arXiv:1707.09724, 2017 | 36 | 2017 |