Generative Adversarial Network Action Set
References
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A. (2017). “Improved Training of Wasserstein GANs.” In Proceedings of the 31st International Conference on Neural Information Processing Systems, 5769–5779. https://proceedings.neurips.cc/paper/2017/file/892c3b1c6dccd52936e27cbd0ff683d6-Paper.pdf.
Karnewar, A., and Wang, O. (2020). “MSG-GAN: Multi-scale Gradients for Generative Adversarial Networks.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). New York: IEEE. https://openaccess.thecvf.com/content_CVPR_2020/papers/Karnewar_MSG-GAN_Multi-Scale_Gradients_for_Generative_Adversarial_Networks_CVPR_2020_paper.pdf.
Karras, T., Aila, T., Laine, S., and Lehtinen, J. (2018). “Progressive Growing of GANs for Improved Quality, Stability, and Variation.” In Proceedings of the Sixth International Conference on Learning Representations. La Jolla, CA: ICLR. https://openreview.net/pdf?id=Hk99zCeAb.
Karras, T., Laine, S., and Aila, T. (2019). “A Style-Based Generator Architecture for Generative Adversarial Networks.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). New York: IEEE. https://openaccess.thecvf.com/content_CVPR_2019/papers/Karras_A_Style-Based_Generator_Architecture_for_Generative_Adversarial_Networks_CVPR_2019_paper.pdf.
Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., and Aila, T. (2020). “Analyzing and Improving the Image Quality of StyleGAN.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). New York: IEEE. https://openaccess.thecvf.com/content_CVPR_2020/papers/Karras_Analyzing_and_Improving_the_Image_Quality_of_StyleGAN_CVPR_2020_paper.pdf.
Kingma, D. P., and Ba, J. (2015). “Adam: A Method for Stochastic Optimization.” In Proceedings of the 3rd International Conference for Learning Representations. Baixas, France: ISCA. https://arxiv.org/abs/1412.6980.
Torfi, A., and Fox, E. A. (2020). “CorGAN: Correlation-Capturing Convolutional Generative Adversarial Networks for Generating Synthetic Healthcare Records.” Accepted to be published in the 33rd International FLAIRS Conference, AI in Healthcare Informatics. https://arxiv.org/abs/2001.09346.
Xu, L., Skoularidou, M., Cuesta-Infante, A., and Veeramachaneni, K. (2019). “Modeling Tabular Data Using Conditional GAN.” In Neural Information Processing Systems (NeurIPS). https://papers.nips.cc/paper/2019/file/254ed7d2de3b23ab10936522dd547b78-Paper.pdf.