2 citations · 5 across the 14 of their papers we have counts for
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cs.CV2022
Progressive Latent Replay for efficient Generative Rehearsal
Stanisław Pawlak, Filip Szatkowski, Michał Bortkiewicz +2
We introduce a new method for internal replay that modulates the frequency of rehearsal based on the depth of the network. While replay strategies mitigate the effects of catastrop…
cs.CV2022★ 2 cited
Selectively increasing the diversity of GAN-generated samples
Jan Dubiński, Kamil Deja, Sandro Wenzel +2
Generative Adversarial Networks (GANs) are powerful models able to synthesize data samples closely resembling the distribution of real data, yet the diversity of those generated sa…