Paper Citation Record · LEDGER

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models

As of 22 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 3 inbound Pith citation observations for arXiv:2411.18440.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.18440 v2

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

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Outbound references

Observation 20100324-205a-4949-ae31-6e782826894e · outbound

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Unresolved cited work

Reference 1

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Unresolved cited work

Reference 2

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Observation c6705125-f822-46e2-b6a2-4aba96451bfe · outbound

This paper cites Aihara et al.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Aihara et al

Reference 3

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Wasserstein gan

Reference 4

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This paper cites Conselice.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Conselice

Reference 5

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Observation be6f004e-427a-4c5f-9294-23c4629c0cb0 · outbound

This paper cites The evolution of galaxy structure over cosmic time.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models The evolution of galaxy structure over cosmic time

Reference 6

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Observation d67ba134-80b1-406a-9e4a-cfad76896d3e · outbound

This paper cites Diffusion Models Beat GANs on Image Synthesis.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Diffusion Models Beat GANs on Image Synthesis

Reference 7

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Observation 83fcd2df-d074-4980-adf0-61b5f801b11d · outbound

This paper cites Jane Wang.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Jane Wang

Reference 8

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This paper cites Galaxiesml: A dataset of galaxy images with matched redshifts.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Galaxiesml: A dataset of galaxy images with matched redshifts

Reference 9

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Observation 6739b066-82b8-4760-a46f-de0ca8b316a9 · outbound

This paper cites GalaxiesML: an imaging and photometric dataset of galaxies for machine learning , June 2024 b.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models GalaxiesML: an imaging and photometric dataset of galaxies for machine learning , June 2024 b

Reference 10

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Observation f0dcdb3d-829a-4bec-b332-0d41c00ab3ef · outbound

This paper cites Taming transformers for high-resolution image synthesis.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Taming transformers for high-resolution image synthesis

Reference 11

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This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio

Reference 12

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This paper cites Gaussian Error Linear Units (GELUs).

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Gaussian Error Linear Units (GELUs)

Reference 13

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This paper cites GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

Reference 14

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Observation 14291387-0bb6-4e67-a995-f27e47cf5007 · outbound

This paper cites Second data release of the Hyper Suprime-Cam Subaru Strategic Program.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Second data release of the Hyper Suprime-Cam Subaru Strategic Program

Reference 15

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Observation f767c8b4-9106-48d8-bc4c-ec9bde1647bb · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Denoising Diffusion Probabilistic Models

Reference 16

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Observation 3115ce72-c07f-4d4a-981a-7a21cba152db · outbound

This paper cites Denoising diffusion probabilistic models.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Denoising diffusion probabilistic models

Reference 17

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Observation 8e548572-fe7e-4879-a85d-dfdd4438a71e · outbound

This paper cites Better Prompt Compression Without Multi-Layer Perceptrons.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Better Prompt Compression Without Multi-Layer Perceptrons

Reference 18

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This paper cites Unlocking the Potential of Text-to-Image Diffusion with PAC-Bayesian Theory.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Unlocking the Potential of Text-to-Image Diffusion with PAC-Bayesian Theory

Reference 19

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This paper cites Analyzing and Improving the Training Dynamics of Diffusion Models.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Analyzing and Improving the Training Dynamics of Diffusion Models

Reference 20

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This paper cites Auto-encoding variational bayes.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Auto-encoding variational bayes

Reference 21

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Observation 4fea6320-0a81-4960-a8f5-ecfa1a18cc7b · outbound

This paper cites Latent plan transformer for trajectory abstraction: Planning as latent space inference.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Latent plan transformer for trajectory abstraction: Planning as latent space inference

Reference 22

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Observation 4fcb3fc1-48a3-4cdd-8863-1d884410fd64 · outbound

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Kuijken et al

Reference 23

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Observation 5a9e660f-b244-4be1-90a6-f98b52c923f4 · outbound

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Deep generative models for galaxy image simulations

Reference 24

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Observation 0da81623-2d34-4ed2-816f-9d68a49a4c1d · outbound

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Lastufka, M

Reference 25

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Distributionally Robust Receive Combining

Reference 26

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This paper cites Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models

Reference 27

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Rl isn't enough

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Unresolved cited work

Reference 29

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This paper cites Narr, Kirsten A.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Narr, Kirsten A

Reference 30

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This paper cites Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models

Reference 31

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Unresolved cited work

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This paper cites Decoupled weight decay regularization.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Decoupled weight decay regularization

Reference 33

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Observation 833acd25-4d51-4a2b-a5b6-6197b50909f5 · outbound

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Lotz, Patrik Jonsson, T

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Cosmic Star-Formation History

Reference 35

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Detecting outliers in astronomical images with deep generative networks

Reference 36

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This paper cites How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds

Reference 37

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Improved Denoising Diffusion Probabilistic Models

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This paper cites Photometric Redshifts for the Hyper Suprime-Cam Subaru Strategic Program Data Release 2.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Photometric Redshifts for the Hyper Suprime-Cam Subaru Strategic Program Data Release 2

Reference 39

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Unresolved cited work

Reference 40

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Observation f5fa1eac-536f-452d-9ae6-3d08d16c6f96 · outbound

This paper cites Monitoring primitive interactions during the training of dnns.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Monitoring primitive interactions during the training of dnns

Reference 41

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Observation 48a8ecb4-02ed-4da7-9957-50fca52e5a19 · outbound

This paper cites Realistic galaxy image simulation via score-based generative models.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Realistic galaxy image simulation via score-based generative models

Reference 42

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This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Deep unsupervised learning using nonequilibrium thermodynamics

Reference 43

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Observation ec8ecdd4-fa9d-431a-8361-ca4dd46bb17f · outbound

This paper cites Weiss, Niru Maheswaranathan, and Surya Ganguli.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Weiss, Niru Maheswaranathan, and Surya Ganguli

Reference 44

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Observation 85a16c35-056c-4b84-9354-922ef8d0b578 · outbound

This paper cites Denoising Diffusion Implicit Models.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Denoising Diffusion Implicit Models

Reference 45

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This paper cites Diffusion Models for Probabilistic Deconvolution of Galaxy Images.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Diffusion Models for Probabilistic Deconvolution of Galaxy Images

Reference 46

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This paper cites Think Twice Before You Act: Improving Inverse Problem Solving With MCMC.

Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models Think Twice Before You Act: Improving Inverse Problem Solving With MCMC

Reference 47

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Pith citing papers

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