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Generative models have proven to be an outstanding tool for representing high-dimensional probability distributions and generating realistic-looking images.
The coincidence approach to stochastic point processes
Macchi, O · 1975
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The MNIST database of handwritten digits
LeCun, Y · 1998
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Determinantal processes and independence
Hough, J. B., Krishnapur, M., Peres, Y., Virág, B., et al · 2006
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Kernel learning by unconstrained optimization
Li, F., Fu, Y., Dai, Y.-H., Sminchisescu, C., and Wang, J · 2009
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Structured determinantal point processes
Kulesza, A. and Taskar, B · 2010
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Learning determinantal point processes
Kulesza, A. and Taskar, B · 2011
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Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2013
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Diverse sequential subset selection for supervised video summarization
Gong, B., Chao, W.-L., Grauman, K., and Sha, F · 2014
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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Improving the estimation of word importance for news multi-document summarization
Hong, K. and Nenkova, A · 2014
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Determinantal point processes
Gupta, S · 2015
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InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets
Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., and Abbeel, P · 2016
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Coupled generative adversarial networks
Liu, M.-Y. and Tuzel, O · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, A., Metz, L., and Chintala, S · 2016
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Improved techniques for training gans
Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., and Chen, X · 2016
Cited alongside, same era.
Video summarization with long short-term memory
Zhang, K., Chao, W.-L., Sha, F., and Grauman, K · 2016
Cited alongside, same era.
Wasserstein GAN
Arjovsky, M., Chintala, S., and Bottou, L · 2017
Cited alongside, same era.
Mode regularized generative adversarial networks
Che, T., Li, Y., Jacob, A. P., Bengio, Y., and Li, W · 2017
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Adversarial feature learning
Donahue, J., Krähenbühl, P., and Darrell, T · 2017
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Adversarially learned inference
Dumoulin, V., Belghazi, I., Poole, B., Mastropietro, O., Lamb, A., Arjovsky, M., and Courville, A · 2017
Cited alongside, same era.
Hierarchical implicit models and likelihood-free variational inference
Tran, D., Ranganath, R., and Blei, D. M · 2017
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Generalized loss-sensitive adversarial learning with manifold margins
Edraki, M. and Qi, G.-J · 2018
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Multi-agent diverse generative adversarial networks
Ghosh, A., Kulharia, V., Namboodiri, V., Torr, P. H., and Dokania, P. K · 2018
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Creating capsule wardrobes from fashion images
Hsiao, W.-L. and Grauman, K · 2018
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Progressive growing of GANs for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2018
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Pacgan: The power of two samples in generative adversarial networks
Lin, Z., Khetan, A., Fanti, G. C., and Oh, S · 2018
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Durugkar, I., Gemp, I., and Mahadevan, S · 2017
Cited alongside, same era.
Improved training of Wasserstein GANs
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A. C · 2017
Cited alongside, same era.
Deligan: Generative adversarial networks for diverse and limited data
Gurumurthy, S., Sarvadevabhatla, R. K., and Babu, R. V · 2017
Cited alongside, same era.
Unsupervised video summarization with adversarial lstm networks
Mahasseni, B., Lam, M., and Todorovic, S · 2017
Cited alongside, same era.
Unrolled generative adversarial networks
Metz, L., Poole, B., Pfau, D., and Sohl-Dickstein, J · 2017
Cited alongside, same era.
Dual discriminator generative adversarial nets
Nguyen, T., Le, T., Vu, H., and Phung, D · 2017
Cited alongside, same era.
Large-scale celebfaces attributes (CelebA) dataset
Liu, Z., Luo, P., Wang, X., and Tang, X · 2018
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Mixed batches and symmetric discriminators for gan training
Lucas, T., Tallec, C., Verbeek, J., and Ollivier, Y · 2018
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Spectral normalization for generative adversarial networks
Miyato, T., Kataoka, T., Koyama, M., and Yoshida, Y · 2018
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Richardson, E. and Weiss, Y · 2018
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Coverage and quality driven training of generative image models
Shmelkov, K., Lucas, T., Alahari, K., Schmid, C., and Verbeek, J · 2018
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Bourgan: Generative networks with metric embeddings
Xiao, C., Zhong, P., and Zheng, C · 2018
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Self-attention generative adversarial networks
Zhang, H., Goodfellow, I., Metaxas, D., and Odena, A · 2018
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