Liqun Chen
Liqun Chen
PhD students in ECE, Duke University
Verified email at duke.edu - Homepage
Title
Cited by
Cited by
Year
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
1602017
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
1012017
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
692018
Adversarial symmetric variational autoencoder
Y Pu, W Wang, R Henao, L Chen, Z Gan, C Li, L Carin
arXiv preprint arXiv:1711.04915, 2017
642017
Symmetric variational autoencoder and connections to adversarial learning
L Chen, S Dai, Y Pu, C Li, Q Su, L Carin
AISTATS 2018, 2017
522017
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
342018
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
322019
Chi-square generative adversarial network
C Tao, L Chen, R Henao, J Feng, L Carin
International Conference on Machine Learning, 4894-4903, 2018
242018
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
242018
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
202018
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
192019
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
122019
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
102017
Graph Optimal Transport for Cross-Domain Alignment
L Chen, Z Gan, Y Cheng, L Li, L Carin, J Liu
ICML 2020, 2020
92020
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
72019
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
52019
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
52019
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
42020
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
42020
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
42018
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