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  1. 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, efficient and computationally cheap emulator for producing novel weak lensing convergence maps as well as cosmic web data in 2-D and 3-D. However, like any algorithm, the GAN approach comes with a set of ...
    Author:Andrius Tamosiunas, Hans A. Winther, Kazuya Koyama, David J. Bacon, Robert C. Nichol, Ben MawdsleyPublished:2020
  2. academic.oup.com

    Furthermore, we explore techniques from contemporary research in the field of deep learning, such as latent space interpolation, as a way to control the outputs of the algorithm and as a tool to explore the structure of the latent space. Finally, we apply the latent space interpolation techniques for producing data of unseen cosmological ...
    Author:Andrius Tamosiunas, Andrius Tamosiunas, Hans A. Winther, Kazuya Koyama, David J. Bacon, Robert C. Ni...Published:2021
  3. ieeexplore.ieee.org

    We show that the latent space interpolation procedure allows the generation of outputs with intermediate cosmological parameters that were not included in the training data. Our results indicate a 1-20 per cent difference between the power spectra of the GAN-produced and the test data samples depending on the data set used and whether ...
  4. ui.adsabs.harvard.edu

    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 ...
    Author:Andrius Tamosiunas, Andrius Tamosiunas, Hans A. Winther, Kazuya Koyama, David J. Bacon, Robert C. Ni...Published:2021
  5. researchportal.port.ac.uk

    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, efficient and computationally cheap emulator for producing novel weak lensing convergence maps as well as cosmic web data in 2-D and 3-D.
    Author:Andrius Tamosiunas, Andrius Tamosiunas, Hans A. Winther, Kazuya Koyama, David J. Bacon, Robert C. Ni...Published:2021
  6. Investigating cosmological GAN emulators using latent space interpolation Andrius Tamosiunas ,1,2 ... show that the latent space interpolation procedure allows the generation of outputs with intermediate cosmological parameters that were not included in the training data. Our results indicate a 1-20 percent difference between the power ...
  7. researchgate.net

    Inv estigating cosmological GAN emulators using latent space interpolation Andrius T amosiunas , 1 , 2 ‹ Hans A. Winther, 3 Kazuya K oyama, 2 David J. Bacon , 2 Robert C. Nichol 2 and Ben Mawdsley 2
  8. semanticscholar.org

    This work trains a GAN to produce weak lensing convergence maps and dark matter overdensity field data for multiple redshifts, cosmological parameters, and modified gravity models, and applies the technique of latent space interpolation as a tool for understanding the feature space of the GAN algorithm. Generative adversarial networks (GANs) have been recently applied as a novel emulation ...
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