# Investigating cosmological GAN emulators using latent space interpolation

@article{Tamoinas2021InvestigatingCG, title={Investigating cosmological GAN emulators using latent space interpolation}, author={Andrius Tamo{\vs}iūnas and Hans A. Winther and Kazuya Koyama and David Bacon and Robert C. Nichol and Ben Mawdsley}, journal={Monthly Notices of the Royal Astronomical Society}, year={2021} }

Generative adversarial networks (GANs) have been recently applied as a novel emulation technique for large-scale structure simulations. Recent results show that GANs can be used as a fast and efficient emulator for producing novel weak lensing convergence maps as well as cosmic web data in 2D and 3D. However, like any algorithm, the GAN approach comes with a set of limitations, such as an unstable training procedure, inherent randomness of the produced outputs, and difficulties when training…

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