| Alice: Towards understanding adversarial learning for joint distribution matching C Li, H Liu, C Chen, Y Pu, L Chen, R Henao, L Carin arXiv preprint arXiv:1709.01215, 2017 | 160 | 2017 |
| Triangle generative adversarial networks Z Gan, L Chen, W Wang, Y Pu, Y Zhang, H Liu, C Li, L Carin Advances in Neural Information Processing Systems, 5253-5262, 2017 | 101 | 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 Advances in Neural Information Processing Systems 2018, 2018 | 69 | 2018 |
| Adversarial symmetric variational autoencoder Y Pu, W Wang, R Henao, L Chen, Z Gan, C Li, L Carin arXiv preprint arXiv:1711.04915, 2017 | 64 | 2017 |
| Symmetric variational autoencoder and connections to adversarial learning L Chen, S Dai, Y Pu, C Li, Q Su, L Carin AISTATS 2018, 2017 | 52 | 2017 |
| A unified particle-optimization framework for scalable Bayesian sampling C Chen, R Zhang, W Wang, B Li, L Chen arXiv preprint arXiv:1805.11659, 2018 | 34 | 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, ... International Conference on Learning Representations, 2019 | 32 | 2019 |
| Chi-square generative adversarial network C Tao, L Chen, R Henao, J Feng, L Carin International Conference on Machine Learning, 4894-4903, 2018 | 24 | 2018 |
| Continuous-time flows for efficient inference and density estimation C Chen, C Li, L Chen, W Wang, Y Pu, LC Duke International Conference on Machine Learning, 824-833, 2018 | 24 | 2018 |
| Variational inference and model selection with generalized evidence bounds L Chen, C Tao, R Zhang, R Henao, L Carin International Conference on Machine Learning, 892-901, 2018 | 20 | 2018 |
| 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 ACL 2019, 2019 | 19 | 2019 |
| 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, ... ACL 2019, 2019 | 12 | 2019 |
| Continuous-time flows for deep generative models C Chen, C Li, L Chen, W Wang, Y Pu, L Carin International Conference on Machine Learning, 2017 | 10 | 2017 |
| Graph Optimal Transport for Cross-Domain Alignment L Chen, Z Gan, Y Cheng, L Li, L Carin, J Liu ICML 2020, 2020 | 9 | 2020 |
| Improving textual network learning with variational homophilic embeddings W Wang, C Tao, Z Gan, G Wang, L Chen, X Zhang, R Zhang, Q Yang, ... arXiv preprint arXiv:1909.13456, 2019 | 7 | 2019 |
| On Fenchel Mini-Max Learning C Tao, L Chen, S Dai, J Chen, K Bai, D Wang, J Feng, W Lu, G Bobashev, ... International Conference on Machine Learning, 2019 | 5 | 2019 |
| Variational annealing of GANs: A Langevin perspective C Tao, S Dai, L Chen, K Bai, J Chen, C Liu, R Zhang, G Bobashev, ... International conference on machine learning, 6176-6185, 2019 | 5 | 2019 |
| Contextualized perturbation for textual adversarial attack D Li, Y Zhang, H Peng, L Chen, C Brockett, MT Sun, B Dolan arXiv preprint arXiv:2009.07502, 2020 | 4 | 2020 |
| Dynamic embedding on textual networks via a gaussian process P Cheng, Y Li, X Zhang, L Chen, D Carlson, L Carin Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7562-7569, 2020 | 4 | 2020 |
| 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 | 4 | 2018 |
Chunyuan LiSenior Researcher @ Microsoft Research, RedmondVerified email at microsoft.com
