| Towards Unifying Hamiltonian Monte Carlo and Slice Sampling Y Zhang, X Wang, C Chen, R Henao, L Carin | 1304* | 2016 |
| Variational Autoencoder for Deep Learning of Images, Labels and Captions Y Pu, Z Gan, R Henao, X Yuan, C Li, A Stevens, L Carin | 982 | 2016 |
| Joint embedding of words and labels for text classification G Wang, C Li, W Wang, Y Zhang, D Shen, X Zhang, R Henao, L Carin arXiv preprint arXiv:1805.04174, 2018 | 525 | 2018 |
| Adversarial feature matching for text generation Y Zhang, Z Gan, K Fan, Z Chen, R Henao, D Shen, L Carin International conference on machine learning, 4006-4015, 2017 | 458 | 2017 |
| Baseline needs more love: On simple word-embedding-based models and associated pooling mechanisms D Shen, G Wang, W Wang, MR Min, Q Su, Y Zhang, C Li, R Henao, ... arXiv preprint arXiv:1805.09843, 2018 | 437 | 2018 |
| Alice: Towards understanding adversarial learning for joint distribution matching C Li, H Liu, C Chen, Y Pu, L Chen, R Henao, L Carin Advances in neural information processing systems 30, 2017 | 281 | 2017 |
| Unsupervised analysis of transcriptomics in bacterial sepsis across multiple datasets reveals three robust clusters TE Sweeney, TD Azad, M Donato, WA Haynes, TM Perumal, R Henao, ... Critical care medicine 46 (6), 915-925, 2018 | 268 | 2018 |
| Host gene expression classifiers diagnose acute respiratory illness etiology EL Tsalik, R Henao, M Nichols, T Burke, ER Ko, MT McClain, LL Hudson, ... Science translational medicine 8 (322), 322ra11-322ra11, 2016 | 253 | 2016 |
| A community approach to mortality prediction in sepsis via gene expression analysis TE Sweeney, TM Perumal, R Henao, M Nichols, JA Howrylak, AM Choi, ... Nature communications 9 (1), 694, 2018 | 197 | 2018 |
| Learning Deep Sigmoid Belief Networks with Data Augmentation Z Gan, R Henao, D Carlson, L Carin Proceedings of the Eighteenth International Conference on Artificial …, 2015 | 132 | 2015 |
| Adversarial time-to-event modeling P Chapfuwa, C Tao, C Li, C Page, B Goldstein, LC Duke, R Henao International Conference on Machine Learning, 735-744, 2018 | 129 | 2018 |
| Learning generic sentence representations using convolutional neural networks Z Gan, Y Pu, R Henao, C Li, X He, L Carin arXiv preprint arXiv:1611.07897, 2016 | 124 | 2016 |
| Adversarial symmetric variational autoencoder Y Pu, W Wang, R Henao, L Chen, Z Gan, C Li, L Carin Advances in neural information processing systems 30, 2017 | 119* | 2017 |
| Deconvolutional paragraph representation learning Y Zhang, D Shen, G Wang, Z Gan, R Henao, L Carin Advances in Neural Information Processing Systems 30, 2017 | 119 | 2017 |
| Wasserstein contrastive representation distillation L Chen, D Wang, Z Gan, J Liu, R Henao, L Carin Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 108 | 2021 |
| Scalable Deep Poisson Factor Analysis for Topic Modeling Z Gan, C Chen, R Henao, D Carlson, L Carin Proceedings of The 32nd International Conference on Machine Learning, 2015 | 107 | 2015 |
| An Integrated Transcriptome and Expressed Variant Analysis of Sepsis Survival and Death EL Tsalik, RJ Langley, DL Dinwiddie, NA Miller, B Yoo, ... Genome medicine 6 (11), 2014 | 102 | 2014 |
| Impact of the COVID-19 pandemic on patterns of outpatient cardiovascular care J Wosik, MEB Clowse, R Overton, B Adagarla, N Economou-Zavlanos, ... American Heart Journal 231, 1-5, 2021 | 100 | 2021 |
| Deep temporal sigmoid belief networks for sequence modeling Z Gan, C Li, R Henao, DE Carlson, L Carin Advances in Neural Information Processing Systems 28, 2015 | 97 | 2015 |
| Convolutional neural network to identify symptomatic Alzheimer’s disease using multimodal retinal imaging CE Wisely, D Wang, R Henao, DS Grewal, AC Thompson, CB Robbins, ... British Journal of Ophthalmology 106 (3), 388-395, 2022 | 96 | 2022 |
Lawrence CarinDuke UniversityПотвърден имейл адрес: duke.edu
