1. Arjovsky, M., Chintala, S., & Bottou, L. (2017). Wasserstein Generative Adversarial Networks. Int. Conf. Mach. Learn.,70, 214–223.
2. Austin, J., Johnson, D. D., Ho, J., Tarlow, D., & van den Berg, R. (2021). Structured Denoising Diffusion Models in Discrete State-Spaces. Adv. Neural Inform. Process. Syst.,34, 17981–17993.
3. Avrahami, O., Lischinski, D., & Fried, O. (2022). Blended Diffusion for Text-Driven Editing of Natural Images. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 18208-18218).
4. Ballester, C., Bertalmio, M., Caselles, V., Sapiro, G., & Verdera, J. (2001). Filling-in by joint interpolation of vector fields and gray levels. IEEE Trans Image Process, 10(8), 1200–1211.
5. Baluja, S., Marwood, D., Johnston, N., Covell, M. (2019). Learning to render better image previews. In I2019 IEEE International Conference on Image Processing (ICIP), (pp. 1700-1704). IEEE.