Zhe Gan
Zhe Gan
Principal Researcher, Microsoft
Verified email at microsoft.com - Homepage
Cited by
Cited by
Attngan: Fine-grained text to image generation with attentional generative adversarial networks
T Xu, P Zhang, Q Huang, H Zhang, Z Gan, X Huang, X He
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Variational Autoencoder for Deep Learning of Images, Labels and Captions
Y Pu, Z Gan, R Henao, X Yuan, C Li, A Stevens, L Carin
NIPS, 2016
Uniter: Universal image-text representation learning
YC Chen, L Li, L Yu, A El Kholy, F Ahmed, Z Gan, Y Cheng, J Liu
European Conference on Computer Vision, 104-120, 2020
Semantic compositional networks for visual captioning
Z Gan, C Gan, X He, Y Pu, K Tran, J Gao, L Carin, L Deng
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Patient knowledge distillation for bert model compression
S Sun, Y Cheng, Z Gan, J Liu
arXiv preprint arXiv:1908.09355, 2019
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
Stylenet: Generating attractive visual captions with styles
C Gan, Z Gan, X He, J Gao, L Deng
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
Generating informative and diverse conversational responses via adversarial information maximization
Y Zhang, M Galley, J Gao, Z Gan, X Li, C Brockett, B Dolan
arXiv preprint arXiv:1809.05972, 2018
Freelb: Enhanced adversarial training for natural language understanding
C Zhu, Y Cheng, Z Gan, S Sun, T Goldstein, J Liu
International Conference on Learning Representations, 2020
Relation-aware graph attention network for visual question answering
L Li, Z Gan, Y Cheng, J Liu
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Generating Text via Adversarial Training
Y Zhang, Z Gan, L Carin
Workshop on Adversarial Training, NIPS 2016, 2016
Learning Generic Sentence Representations Using Convolutional Neural Networks
Z Gan, Y Pu, R Henao, C Li, X He, L Carin
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017
Triangle generative adversarial networks
Z Gan, L Chen, W Wang, Y Pu, Y Zhang, H Liu, C Li, L Carin
arXiv preprint arXiv:1709.06548, 2017
Learning deep sigmoid belief networks with data augmentation
Z Gan, R Henao, D Carlson, L Carin
Artificial Intelligence and Statistics, 268-276, 2015
Large-scale adversarial training for vision-and-language representation learning
Z Gan, YC Chen, L Li, C Zhu, Y Cheng, J Liu
arXiv preprint arXiv:2006.06195, 2020
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
Discourse-aware neural extractive text summarization
J Xu, Z Gan, Y Cheng, J Liu
arXiv preprint arXiv:1910.14142, 2019
Deconvolutional paragraph representation learning
Y Zhang, D Shen, G Wang, Z Gan, R Henao, L Carin
arXiv preprint arXiv:1708.04729, 2017
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
Tactical rewind: Self-correction via backtracking in vision-and-language navigation
L Ke, X Li, Y Bisk, A Holtzman, Z Gan, J Liu, J Gao, Y Choi, S Srinivasa
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
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