Publisher
Springer Nature Switzerland
Reference41 articles.
1. Goodfellow, I.J., et al.: Generative adversarial networks. Commun. ACM 63(11), 139–144 (2020). OCLC: 8694362134
2. Brownlee, J.: How to code the GAN training algorithm and loss functions (2020)
3. Parthasarathy, D., Backstrom, K., Henriksson, J., Einarsdottir, S.: Controlled time series generation for automotive software-in-the-loop testing using GANs. In: 2020 IEEE International Conference On Artificial Intelligence Testing (AITest), pp. 39–46 (2020). OCLC: 8658758958
4. Abdollahpouri, H., et al.: Multistakeholder recommendation: survey and research directions (2020). OCLC: 1196494457
5. Aldausari, N., Sowmya, A., Marcus, N., Mohammadi, G.: Video generative adversarial networks: a review. ACM Comput. Surv. 55 (2023). https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128166282, https://doi.org/10.1145/3487891