Fetching the paper…
Reading the bibliography…
Deep generative models are powerful tools that have produced impressive results in recent years.
Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
Earlier work this paper cites.
Unlearning for better mixing
Breuleux, O., Bengio, Y., and Vincent, P · 2010
Earlier work this paper cites.
Intriguing properties of neural networks
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I. J., and Fergus, R · 2013
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al · 2015
Earlier work this paper cites.
A note on the evaluation of generative models
Theis, L., Oord, A. v. d., and Bethge, M · 2015
Earlier work this paper cites.
Locally-connected transformations for deep gmms
van den Oord, A. and Dambre, J · 2015
Earlier work this paper cites.
Mode regularized generative adversarial networks
Che, T., Li, Y., Jacob, A. P., Bengio, Y., and Li, W · 2016
Earlier work this paper cites.
Generative adversarial metric
Im, D. J., Kim, C. D., Jiang, H., and Memisevic, R · 2016
Earlier work this paper cites.
Image-to-image translation with conditional adversarial networks
Isola, P., Zhu, J., Zhou, T., and Efros, A. A · 2016
Cited alongside, same era.
Photo-realistic single image super-resolution using a generative adversarial network
Ledig, C., Theis, L., Huszar, F., Caballero, J., Aitken, A. P., Tejani, A., Totz, J., Wang, Z., and Shi, W · 2016
Cited alongside, same era.
C-RNN-GAN: continuous recurrent neural networks with adversarial training
Mogren, O · 2016
Cited alongside, same era.
Improved techniques for training gans
Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., and Chen, X · 2016
Cited alongside, same era.
Rethinking the inception architecture for computer vision
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., and Wojna, Z · 2016
Cited alongside, same era.
Long text generation via adversarial training with leaked information
Guo, J., Lu, S., Cai, H., Zhang, W., Yu, Y., and Wang, J · 2017
Later among the works it cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2017
Later among the works it cites.
Progressive growing of gans for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2017
Later among the works it cites.
Are gans created equal? a large-scale study
Lucic, M., Kurach, K., Michalski, M., Gelly, S., and Bousquet, O · 2017
Later among the works it cites.
Automatic differentiation in pytorch
Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., and Lerer, A · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Arjovsky, M., Chintala, S., and Bottou, L · 2017
Cited alongside, same era.
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs
Esteban, C., Hyland, S. L., and Rätsch, G · 2017
Cited alongside, same era.
Deep learning the physics of transport phenomena
Farimani, A. B., Gomes, J., and Pande, V. S · 2017
Cited alongside, same era.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y
Cited in the paper.
Explaining and harnessing adversarial examples
Goodfellow, I. J., Shlens, J., and Szegedy, C
Cited in the paper.
Later among the works it cites.
Variational approaches for auto-encoding generative adversarial networks
Rosca, M., Lakshminarayanan, B., Warde-Farley, D., and Mohamed, S · 2017
Later among the works it cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Zhu, J., Park, T., Isola, P., and Efros, A. A · 2017
Later among the works it cites.
An empirical study on evaluation metrics of generative adversarial networks
Qiantong, X., Gao, H., Yang, Y., Chuan, G., Yu, S., Felix, W., and Weinberger, K · 2018
Closest in time.