Awesome astro-ph.CO

Papers

Bayesian Inference of Primordial Magnetic Field Parameters from CMB with Spherical Graph Neural Networks (2025)
Juan Alejandro Pinto Castro et al.
1.44
Score Matching on Large Geometric Graphs for Cosmology Generation (2025)
Diana-Alexandra Onutu et al.
1.33
Discovering Symbolic Models from Deep Learning with Inductive Biases (2020)
Miles Cranmer et al.
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The GCE in a New Light: Disentangling the $\gamma$-ray Sky with Bayesian Graph Convolutional Neural Networks (2020)
Florian List et al.
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Unsupervised Resource Allocation with Graph Neural Networks (2021)
Miles Cranmer (Princeton) et al.
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Inferring halo masses with Graph Neural Networks (2021)
Pablo Villanueva-Domingo et al.
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Weighing the Milky Way and Andromeda with Artificial Intelligence (2021)
Pablo Villanueva-Domingo et al.
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Learning cosmology and clustering with cosmic graphs (2022)
Pablo Villanueva-Domingo et al.
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The Cosmic Graph: Optimal Information Extraction from Large-Scale Structure using Catalogues (2022)
T. Lucas Makinen et al.
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Uncovering dark matter density profiles in dwarf galaxies with graph neural networks (2022)
Tri Nguyen et al.
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Robust field-level inference with dark matter halos (2022)
Helen Shao et al.
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Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks (2022)
Ji Won Park et al.
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Cosmic Microwave Background Recovery: A Graph-Based Bayesian Convolutional Network Approach (2023)
Jadie Adams et al.
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Robust Field-level Likelihood-free Inference with Galaxies (2023)
Natal\'i S. M. de Santi et al.
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Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects (2023)
Natal\'i S. M. de Santi et al.
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Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets (2023)
Andrea Roncoli et al.
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Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks (2024)
Nikhil Garuda et al.
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