| 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, ... ACL, 2018 | 81 | 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 | 55 | 2018 |
| Deconvolutional paragraph representation learning Y Zhang, D Shen, G Wang, Z Gan, R Henao, L Carin Advances in Neural Information Processing Systems, 4169-4179, 2017 | 50 | 2017 |
| Adversarial Text Generation via Feature-Mover's Distance L Chen, S Dai, C Tao, H Zhang, Z Gan, D Shen, Y Zhang, G Wang, ... Advances in Neural Information Processing Systems, 4666-4677, 2018 | 24 | 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 | 12 | 2019 |
| 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 | 12 | 2018 |
| JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets Y Pu, S Dai, Z Gan, W Wang, G Wang, Y Zhang, R Henao, L Carin arXiv preprint arXiv:1806.02978, 2018 | 11 | 2018 |
| 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 | 6 | 2019 |
| Learning to Sample with Adversarially Learned Likelihood-Ratio C Li, J Li, G Wang, L Carin | 5 | 2018 |
| Generative Adversarial Network Training is a Continual Learning Problem KJ Liang, C Li, G Wang, L Carin arXiv preprint arXiv:1811.11083, 2018 | 4 | 2018 |
| Adversarial Learning of a Sampler Based on an Unnormalized Distribution C Li, K Bai, J Li, G Wang, C Chen, L Carin arXiv preprint arXiv:1901.00612, 2019 | 3 | 2019 |
| Improving textual network learning with variational homophilic embeddings W Wang, C Tao, Z Gan, G Wang, L Chen, X Zhang, R Zhang, Q Yang, ... Advances in Neural Information Processing Systems, 2074-2085, 2019 | 2 | 2019 |
| Sequence Generation with Guider Network R Zhang, C Chen, Z Gan, W Wang, L Chen, D Shen, G Wang, L Carin arXiv preprint arXiv:1811.00696, 2018 | 2 | 2018 |
| Dual-scale Galerkin methods for Darcy flow G Wang, G Scovazzi, L Nouveau, CE Kees, S Rossi, O Colomés, A Main Journal of Computational Physics 354, 111-134, 2018 | 2 | 2018 |
| Improving Textual Network Embedding with Global Attention via Optimal Transport L Chen, G Wang, C Tao, D Shen, P Cheng, X Zhang, W Wang, Y Zhang, ... arXiv preprint arXiv:1906.01840, 2019 | 1 | 2019 |
| Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods K Liang, G Wang, Y Li, R Henao, L Carin Advances in Neural Information Processing Systems, 3387-3398, 2019 | 1 | 2019 |
| Graph-Driven Generative Models for Heterogeneous Multi-Task Learning W Wang, H Xu, Z Gan, B Li, G Wang, L Chen, Q Yang, W Wang, L Carin arXiv preprint arXiv:1911.08709, 2019 | | 2019 |
| Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding D Sundararaman, V Subramanian, G Wang, S Si, D Shen, D Wang, ... arXiv preprint arXiv:1911.06156, 2019 | | 2019 |
| An Optimal Transport Framework for Zero-Shot Learning W Wang, H Xu, G Wang, W Wang, L Carin arXiv preprint arXiv:1910.09057, 2019 | | 2019 |
| Discriminative Clustering for Robust Unsupervised Domain Adaptation R Wang, G Wang, R Henao arXiv preprint arXiv:1905.13331, 2019 | | 2019 |
