Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-28T22:02:22.676596Z
Paper Citation Record · LEDGER
As of 20 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2605.31420.
A citation records a reference. It does not transfer a finding from one paper to another.
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Source: paper_references, paper_reference_links, observed 2026-06-28T22:02:22.676596Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
64 of 64 outbound references displayed
External citation measurements
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Reference 1
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 A benchmark analysis of saliency-based explainable deep learning methods for the morphological classification of radio galaxies
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2011, The EFIGI catalogue of 4458 nearby galaxies with detailed morphology, A&A, 532, A74
Reference 3
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2025, title The Blue Jay Survey: Deep JWST Spectroscopy for a Representative Sample of Galaxies at Cosmic Noon , arXiv e-prints, arXiv:2510.11775, 10.48550/arXiv.2510.11775
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Unresolved cited work
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 arXiv e-prints , keywords =
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 S., & Welling, M
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Unresolved cited work
Reference 10
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Unresolved cited work
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2023, Discovery of the highest redshift galaxies with JWST, AAS Meeting Abstracts, 241, 153–07
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2026, An updated efficient galaxy morphology classification model based on ConvNeXt encoding with UMAP dimensionality reduction, AJ, 171, 59
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2018, The size evolution of star-forming and quenched galaxies in the IllustrisTNG simulation, MNRAS, 474, 3976
Reference 16
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 DAWN JWST Archive: Morphology from profile fitting of over 340 000 galaxies in major fields
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2017, The Early Evolution of Galactic Disks: Structure, Dynamics and Feedback, Disk Instabilities Across Cosmic Scales, 5
Reference 18
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2025, Galaxy Morphological Classification with Zernike Moments and Machine Learning, ApJS, 277, 10
Reference 19
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2017, On Calibration of Modern Neural Networks, in Proc
Reference 21
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 and Ozernoy L.M., 1981, Accretion of the cloud of gas debris of stars disrupted by the tidal forces of a supermassive black hole, A&A, 95, 39
Reference 22
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Auto-Encoding Variational Bayes
Reference 23
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2024, Hot gas accretion fuels star formation faster than cold accretion in high-redshift galaxies, MNRAS, 534, 918
Reference 24
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2024, JWST reveals a surprisingly high fraction of galaxies being spiral-like at 0.5 z 4 , ApJL, 968, L15
Reference 25
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 H., Park, C., Hwang, H
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2023, Cold gas disks in main-sequence galaxies at cosmic noon, A&A, 672, A106
Reference 27
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2011, Galaxy Zoo 1: data release of morphological classifications for nearly 900,000 galaxies, MNRAS, 410, 166
Reference 28
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2022, A ConvNet for the 2020s, in Proc
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Reference 30
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Unresolved cited work
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Unresolved cited work
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Disk-like galaxies at 4 < z < 7.7 : JWST/NIRCam morphologies revealed by denoising VAE-GCNN classification
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2010, Galaxy Formation and Evolution, Cambridge Univ
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Unresolved cited work
Reference 39
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 E(2) Equivariant Neural Networks for Robust Galaxy Morphology Classification
Reference 41
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 1988, TTidal disruption of stars by black holes of 106-108 solar masses in nearby galaxies, Nature, 333, 523
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2023, Data from the JWST Advanced Deep Extragalactic Survey (JADES), MAST Release
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Detection of Anisotropies in the Circumgalactic Medium of Disk Galaxies: Supermassive Black Hole Activity or Star Formation-driven Outflows?
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 Morphology across cosmic time: assessing the evolution and interplay of disk and bulge-dominated galaxies in the CANDELS survey
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2005, The classification of galaxies: Early history and ongoing developments, Annu
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2007, The Cosmic Evolution Survey (COSMOS): Overview, ApJS, 172, 1
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2026, The MAGPI Survey: co-evolution of baryons and dark matter in star-forming disk-like galaxies at 0.1 < z < 0.85,, arXiv:2601.12315
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2025, COSMOS2025: The COSMOS-Web galaxy catalog, A&A, 704, A339
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 S., & Gallagher, J
Reference 54
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2024, The structure and morphology of galaxies during the Epoch of Reionization revealed by JWST, ApJ, 960, 104
Reference 55
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2025, Automatic machine learning framework to study AGN host morphology, ApJ, 981, 5
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2026, Structural Evolution of Stellar Disks from z 3 to the Present with JWST, MNRAS, in press
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2014, 3D-HST + CANDELS: Evolution of the size–mass distribution since z=3 , ApJ, 788, 28
Reference 58
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2024, On the Nature of Disks at High Redshift Seen by JWST/CEERS with Contrastive Learning and Cosmological Simulations, ApJ, 961, 51
Reference 59
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2022, Galaxy Zoo DECaLS: Detailed visual morphology for 314,000 galaxies, MNRAS, 509, 3966
Reference 60
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2021, General E(2)-Equivariant Steerable CNNs, in Advances in Neural Information Processing Systems (NeurIPS), 14334
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 2024, A galaxy image augmentation method using few-shot learning and GANs, RAA, 24, 035015
Reference 63
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Enhancing Galaxy Classification with U-Net Variational Autoencoders. III. Disk-like Galaxy Identification in JWST Samples of up to redshift 4 and Ji, Zhiyuan and Bunker, Andrew J
Reference 64
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No inbound Pith citation observations are available.