| 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 | 215 | 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 | 176 | 2018 |
| 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 | 147 | 2018 |
| Reinforced cross-modal matching and self-supervised imitation learning for vision-language navigation X Wang, Q Huang, A Celikyilmaz, J Gao, D Shen, YF Wang, WY Wang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 134 | 2019 |
| Understanding the solvent-assisted crystallization mechanism inherent in efficient organic–inorganic halide perovskite solar cells D Shen, X Yu, X Cai, M Peng, Y Ma, X Su, L Xiao, D Zou Journal of Materials Chemistry A 2 (48), 20454-20461, 2014 | 127 | 2014 |
| Deconvolutional paragraph representation learning Y Zhang, D Shen, G Wang, Z Gan, R Henao, L Carin arXiv preprint arXiv:1708.04729, 2017 | 73 | 2017 |
| Adversarial text generation via feature-mover's distance L Chen, S Dai, C Tao, D Shen, Z Gan, H Zhang, Y Zhang, L Carin arXiv preprint arXiv:1809.06297, 2018 | 65 | 2018 |
| Video generation from text Y Li, M Min, D Shen, D Carlson, L Carin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 57 | 2018 |
| Topic compositional neural language model W Wang, Z Gan, W Wang, D Shen, J Huang, W Ping, S Satheesh, L Carin International Conference on Artificial Intelligence and Statistics, 356-365, 2018 | 53 | 2018 |
| Topic compositional neural language model W Wang, Z Gan, W Wang, D Shen, J Huang, W Ping, S Satheesh, L Carin International Conference on Artificial Intelligence and Statistics, 356-365, 2018 | 53 | 2018 |
| Topic-guided variational autoencoders for text generation W Wang, Z Gan, H Xu, R Zhang, G Wang, D Shen, C Chen, L Carin arXiv preprint arXiv:1903.07137, 2019 | 50 | 2019 |
| Deconvolutional latent-variable model for text sequence matching D Shen, Y Zhang, R Henao, Q Su, L Carin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 50 | 2018 |
| Efficient fiber shaped zinc bromide batteries and dye sensitized solar cells for flexible power sources M Peng, K Yan, H Hu, D Shen, W Song, D Zou Journal of Materials Chemistry C 3 (10), 2157-2165, 2015 | 40 | 2015 |
| Nash: Toward end-to-end neural architecture for generative semantic hashing D Shen, Q Su, P Chapfuwa, W Wang, G Wang, L Carin, R Henao arXiv preprint arXiv:1805.05361, 2018 | 32 | 2018 |
| Improving sequence-to-sequence learning via optimal transport L Chen, Y Zhang, R Zhang, C Tao, Z Gan, H Zhang, B Li, D Shen, C Chen, ... arXiv preprint arXiv:1901.06283, 2019 | 31 | 2019 |
| Towards generating long and coherent text with multi-level latent variable models D Shen, A Celikyilmaz, Y Zhang, L Chen, X Wang, J Gao, L Carin arXiv preprint arXiv:1902.00154, 2019 | 21* | 2019 |
| Diffusion maps for textual network embedding X Zhang, Y Li, D Shen, L Carin arXiv preprint arXiv:1805.09906, 2018 | 21 | 2018 |
| Learning context-sensitive convolutional filters for text processing D Shen, MR Min, Y Li, L Carin arXiv preprint arXiv:1709.08294, 2017 | 21* | 2017 |
| An end-to-end generative architecture for paraphrase generation Q Yang, D Shen, Y Cheng, W Wang, G Wang, L Carin Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 18 | 2019 |
| Improved semantic-aware network embedding with fine-grained word alignment D Shen, X Zhang, R Henao, L Carin arXiv preprint arXiv:1808.09633, 2018 | 18 | 2018 |
Lawrence CarinProfessor of Electrical and Computer Engineering, Duke UniversityVerified email at ece.duke.edu
