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Adaptive Graph Neural Networks for Cosmological Data Generalization: Additional Plots

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This paper is available on arxiv under CC 4.0 license.

Authors:

(1) Andrea Roncoli, Department of Computer, Science (University of Pisa);

(2) Aleksandra Ciprijanovi´c´, Computational Science and AI Directorate (Fermi National Accelerator Laboratory) and Department of Astronomy and Astrophysics (University of Chicago);

(3) Maggie Voetberg, Computational Science and AI Directorate, (Fermi National Accelerator Laboratory);

(4) Francisco Villaescusa-Navarro, Center for Computational Astrophysics (Flatiron Institute);

(5) Brian Nord, Computational Science and AI Directorate, Fermi National Accelerator Laboratory, Department of Astronomy and Astrophysics (University of Chicago) and Kavli Institute for Cosmological Physics (University of Chicago).

Table of Links

Abstract and Intro

Data and Methods

Results

Conclusions

Acknowledgments and Disclosure of Funding, and References

Additional Plots

A. Additional Plots

L O A D I N G
. . . comments & more!

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Cosmological thinking: time, space and universal causation  HackerNoon profile picture
Cosmological thinking: time, space and universal causation @cosmological
From Big Bang's singularity to galaxies' cosmic dance the universe unfolds its majestic tapestry of space and time.

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