Examining Effects of Class Imbalance on Conditional GAN Training
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-42505-9_40
Reference22 articles.
1. Huang, G., Jafari, A.H.: Enhanced balancing GAN: minority-class image generation. Neural Comput. Appl. 1–10 (2021). https://doi.org/10.1007/s00521-021-06163-8
2. Mariani, G., Scheidegger, F., Istrate, R., Bekas, C., Malossi, C.: Bagan: data augmentation with balancing GAN, arXiv preprintar Xiv:1803.09655 (2018)
3. Ahmadzadeh, A., et al.: Challenges with extreme class-imbalance and temporal coherence: a study on solar flare data. In: 2019 IEEE International Conference on Big Data (Big Data), pp. 1423–1431 (2019). https://doi.org/10.1109/BigData47090.2019.9006505
4. Ahmadzadeh, A., et al.: How to train your flare prediction model: revisiting robust sampling of rare events. Astrophys. J. Supplement Ser. 254(2), 23 (2021). https://doi.org/10.3847/1538-4365/abec88
5. Angryk, R.A., et al.: Multivariate time series dataset for space weather data analytics. Sci. Data 7(1) (2020). https://doi.org/10.1038/s41597-020-0548-x
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