Yunchen Pu
Cited by
Cited by
Variational autoencoder for deep learning of images, labels and captions
Y Pu, Z Gan, R Henao, X Yuan, C Li, A Stevens, L Carin
Advances in neural information processing systems 29, 2352-2360, 2016
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
Alice: Towards understanding adversarial learning for joint distribution matching
C Li, H Liu, C Chen, Y Pu, L Chen, R Henao, L Carin
Advances in Neural Information Processing Systems 30, 5495-5503, 2017
VAE learning via Stein variational gradient descent
Y Pu, Z Gan, R Henao, C Li, S Han, L Carin
arXiv preprint arXiv:1704.05155, 2017
Learning generic sentence representations using convolutional neural networks
Z Gan, Y Pu, R Henao, C Li, X He, L Carin
arXiv preprint arXiv:1611.07897, 2016
Zero-shot learning via class-conditioned deep generative models
W Wang, Y Pu, VK Verma, K Fan, Y Zhang, C Chen, P Rai, L Carin
Thirty-second AAAI conference on artificial intelligence, 2018
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
Symmetric variational autoencoder and connections to adversarial learning
L Chen, S Dai, Y Pu, E Zhou, C Li, Q Su, C Chen, L Carin
International Conference on Artificial Intelligence and Statistics, 661-669, 2018
l-net: Reconstruct hyperspectral images from a snapshot measurement
X Miao, X Yuan, Y Pu, V Athitsos
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Parallel lensless compressive imaging via deep convolutional neural networks
X Yuan, Y Pu
Optics express 26 (2), 1962-1977, 2018
A deep generative deconvolutional image model
Y Pu, W Yuan, A Stevens, C Li, L Carin
Artificial Intelligence and Statistics, 741-750, 2016
Learning weight uncertainty with stochastic gradient mcmc for shape classification
C Li, A Stevens, C Chen, Y Pu, Z Gan, L Carin
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
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
Adaptive feature abstraction for translating video to text
Y Pu, MR Min, Z Gan, L Carin
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Implicit causal models for genome-wide association studies
D Tran, DM Blei
arXiv preprint arXiv:1710.10742, 2017
Scalable bayesian learning of recurrent neural networks for language modeling
Z Gan, C Li, C Chen, Y Pu, Q Su, L Carin
arXiv preprint arXiv:1611.08034, 2016
Jointgan: Multi-domain joint distribution learning with generative adversarial nets
Y Pu, S Dai, Z Gan, W Wang, G Wang, Y Zhang, R Henao, LC Duke
International Conference on Machine Learning, 4151-4160, 2018
Tensor-dictionary learning with deep kruskal-factor analysis
A Stevens, Y Pu, Y Sun, G Spell, L Carin
Artificial Intelligence and Statistics, 121-129, 2017
Generative deep deconvolutional learning
Y Pu, X Yuan, L Carin
arXiv preprint arXiv:1412.6039, 2014
Continuous-time flows for deep generative models
C Chen, C Li, L Chen, W Wang, Y Pu, L Carin
arXiv preprint arXiv:1709.01179, 2017
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