| Fast, Accurate, and, Lightweight Super-Resolution with Cascading Residual Network N Ahn, B Kang, KA Sohn European Conference on Computer Vision, 2018 | 638 | 2018 |
| Comparative analysis of metazoan chromatin organization JWK Ho, YL Jung, T Liu, BH Alver, S Lee, K Ikegami, KA Sohn, A Minoda, ... Nature 512 (7515), 449-452, 2014 | 357 | 2014 |
| A multivariate regression approach to association analysis of a quantitative trait network S Kim, KA Sohn, EP Xing Bioinformatics 25 (12), i204-i212, 2009 | 194 | 2009 |
| Predicting Alzheimer’s disease progression using multi-modal deep learning approach G Lee, K Nho, B Kang, KA Sohn, D Kim Scientific reports 9 (1), 1-12, 2019 | 182 | 2019 |
| Ntire 2020 challenge on real-world image super-resolution: Methods and results A Lugmayr, M Danelljan, R Timofte Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 104 | 2020 |
| Joint estimation of structured sparsity and output structure in multiple-output regression via inverse-covariance regularization KA Sohn, S Kim Artificial Intelligence and Statistics, 1081-1089, 2012 | 96 | 2012 |
| Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction D Kim, JG Joung, KA Sohn, H Shin, YR Park, MD Ritchie, JH Kim Journal of the American Medical Informatics Association 22 (1), 109-120, 2015 | 88 | 2015 |
| Method and apparatus for detecting people using stereo camera G Park, K Sohn US Patent App. 11/068,915, 2005 | 66 | 2005 |
| Biological brain age prediction using cortical thickness data: A large scale cohort study HM Aycheh, JK Seong, JH Shin, DL Na, B Kang, SW Seo, KA Sohn Frontiers in aging neuroscience 10, 252, 2018 | 65 | 2018 |
| Bayesian multi-population haplotype inference via a hierarchical Dirichlet process mixture EP Xing, KA Sohn, MI Jordan, YW Teh Proceedings of the 23rd international conference on Machine learning, 1049-1056, 2006 | 55 | 2006 |
| Rethinking data augmentation for image super-resolution: A comprehensive analysis and a new strategy J Yoo, N Ahn, KA Sohn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 52 | 2020 |
| Enhancing the performance of convolutional neural networks on quality degraded datasets J Yim, KA Sohn 2017 International Conference on Digital Image Computing: Techniques and …, 2017 | 51 | 2017 |
| Fast detection of high-order epistatic interactions in genome-wide association studies using information theoretic measure S Leem, H Jeong, J Lee, K Wee, KA Sohn Computational biology and chemistry 50, 19-28, 2014 | 48 | 2014 |
| Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancer M Shivakumar, Y Lee, L Bang, T Garg, KA Sohn, D Kim BMC medical genomics 10 (1), 65-75, 2017 | 47 | 2017 |
| Computing distances between surfaces using line geometry KA Sohn, B Juttler, MS Kim, W Wang 10th Pacific Conference on Computer Graphics and Applications, 2002 …, 2002 | 47 | 2002 |
| hiHMM: Bayesian non-parametric joint inference of chromatin state maps KA Sohn, JWK Ho, D Djordjevic, H Jeong, PJ Park, JH Kim Bioinformatics 31 (13), 2066-2074, 2015 | 45 | 2015 |
| Image super-resolution via progressive cascading residual network N Ahn, B Kang, KA Sohn IEEE Conference on Computer Vision and Pattern Recognition Workshops (NTIRE), 2018 | 41 | 2018 |
| Hidden Markov Dirichlet process: Modeling genetic inference in open ancestral space KA Sohn, EP Xing Bayesian Analysis 2 (3), 501-527, 2007 | 38 | 2007 |
| Incorporating inter-relationships between different levels of genomic data into cancer clinical outcome prediction D Kim, H Shin, KA Sohn, A Verma, MD Ritchie, JH Kim Methods 67 (3), 344-353, 2014 | 32 | 2014 |
| Feature detector using adaptive accelerated segment test Y Biadgie, KA Sohn 2014 International Conference on Information Science & Applications (ICISA), 1-4, 2014 | 31 | 2014 |
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