Paper Citation Record · LEDGER

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks

As of 13 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 2 inbound Pith citation observations for arXiv:2411.12629.

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

pith.paper-citation-record.v1
2411.12629 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:25:03.244943Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:21:35.112001Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 2fc9d975-5061-44b8-819d-0fd4d5c2b54b · outbound

This paper cites Painting galaxies into dark matter haloes using machine learning.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Painting galaxies into dark matter haloes using machine learning

Reference 1

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Observation 9e925d27-f367-4fd0-8b9b-95640a1ea7ee · outbound

This paper cites The Sunyaev–Zel’dovich effect.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks The Sunyaev–Zel’dovich effect

Reference 2

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Observation 9278c98e-b0c9-4eef-bae9-2a86690fda10 · outbound

This paper cites an unresolved cited work.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Unresolved cited work

Reference 3

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Observation 2058dbc6-d832-466d-bc35-60d62d4b90ac · outbound

This paper cites Bullock and Michael Boylan-Kolchin.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Bullock and Michael Boylan-Kolchin

Reference 4

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Observation 4b893934-8cac-4781-9f26-883bce9fdb8c · outbound

This paper cites an unresolved cited work.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Unresolved cited work

Reference 5

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Observation 2acbb200-39f9-4490-9eba-add1865c9ec5 · outbound

This paper cites Cluster- GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Cluster- GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

Reference 6

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Observation 1be582d8-baf7-4e69-936d-e747c31d475c · outbound

This paper cites ´Ciprijanovi´c, D.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks ´Ciprijanovi´c, D

Reference 7

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Observation ad62d8e0-1691-4880-acfa-441a7a364ddf · outbound

This paper cites Gonzalez, Maxim Markevitch, Scott W.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Gonzalez, Maxim Markevitch, Scott W

Reference 8

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Observation c04b0268-79e6-4768-a226-cde48569f529 · outbound

This paper cites Large Synoptic Survey Telescope: Dark Energy Science Collaboration, November 2012.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Large Synoptic Survey Telescope: Dark Energy Science Collaboration, November 2012

Reference 9

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Observation 2e8bc97e-14d8-452e-b08b-afb15153e31d · outbound

This paper cites Discovering Symbolic Models from Deep Learning with Inductive Biases, 2020.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Discovering Symbolic Models from Deep Learning with Inductive Biases, 2020

Reference 10

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Observation da75136d-53e2-43df-8d7e-c356cdb0c657 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geomet- ric, 2019.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Fast Graph Representation Learning with PyTorch Geomet- ric, 2019

Reference 11

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Observation 5664f005-f41c-4a80-86c0-be080492e155 · outbound

This paper cites Gaussian Error Linear Units (GELUs), 2016.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Gaussian Error Linear Units (GELUs), 2016

Reference 12

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Observation fb5e1074-4458-475b-b2d1-d92c0861d6b2 · outbound

This paper cites Benchmarks and explanations for deep learning estimates of X-ray galaxy cluster masses.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Benchmarks and explanations for deep learning estimates of X-ray galaxy cluster masses

Reference 13

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Observation 19e4a15c-077d-4b1e-8cd3-f6c783e2af65 · outbound

This paper cites Random decision forests.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Random decision forests

Reference 14

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Observation da8b40b5-82ab-411b-a28e-7bc52b7fe062 · outbound

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Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Unresolved cited work

Reference 15

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Observation 964fa108-7cfd-47ba-a760-54fe63e48c75 · outbound

This paper cites Kamdar, Matthew J.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Kamdar, Matthew J

Reference 16

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Observation 16d1d3c9-bc65-4481-8e25-613c13379741 · outbound

This paper cites Kouw and Marco Loog.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Kouw and Marco Loog

Reference 17

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Observation 0ecc6e17-c30b-46b5-b065-ba50a6b09263 · outbound

This paper cites Larson, John F.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Larson, John F

Reference 18

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Observation 1ffac219-e325-4699-8dd7-6b2f5e41ae98 · outbound

This paper cites Decoupled Weight Decay Regularization, January 2019.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Decoupled Weight Decay Regularization, January 2019

Reference 19

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Observation fa9ae16d-4b94-4f97-8ee1-80b42aeb2bd8 · outbound

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Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Unresolved cited work

Reference 20

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Observation 4f4596e2-a208-4f02-893c-c6392b0e4f3d · outbound

This paper cites Lovell, Stephen M.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Lovell, Stephen M

Reference 21

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Observation b7414e26-a6aa-4093-b2ef-be35c3981f55 · outbound

This paper cites Marriage, Viviana Acquaviva, Peter A.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Marriage, Viviana Acquaviva, Peter A

Reference 22

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Observation 6324fc67-c41c-4ed2-aa0e-4aff9319ed1b · outbound

This paper cites GalaxyNet: Connecting galaxies and dark matter haloes with deep neural networks and reinforcement learning in large volumes.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks GalaxyNet: Connecting galaxies and dark matter haloes with deep neural networks and reinforcement learning in large volumes

Reference 23

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Observation ed67a3e9-d1b9-4480-ba58-0313058f1302 · outbound

This paper cites Introducing the TNG-Cluster simulation: Overview and the physical properties of the gaseous intracluster medium.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Introducing the TNG-Cluster simulation: Overview and the physical properties of the gaseous intracluster medium

Reference 24

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Observation 09052eb4-cd4c-4485-ab07-f9c1c46a467e · outbound

This paper cites The IllustrisTNG simulations: Public data release.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks The IllustrisTNG simulations: Public data release

Reference 25

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Observation 132df8bb-1674-482c-a0e1-5216bc21ebb2 · outbound

This paper cites Ntampaka, J.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Ntampaka, J

Reference 26

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Observation 97201b74-856c-463e-ab50-d3dd11a3e43e · outbound

This paper cites Scikit-learn: Machine Learning in Python.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Scikit-learn: Machine Learning in Python

Reference 27

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Observation d1092f1c-e511-4c52-ab5c-01b51a6555c8 · outbound

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Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Unresolved cited work

Reference 28

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Observation 8587e2da-cf5d-498c-aa65-4399a828fc4f · outbound

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Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Unresolved cited work

Reference 29

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Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Unresolved cited work

Reference 30

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Observation dcceaeb1-32de-48dd-9020-6f303257109d · outbound

This paper cites Sampaio-Santos, Y.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Sampaio-Santos, Y

Reference 31

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Observation d6d4d864-2119-4e47-9d33-3ec9788fd57f · outbound

This paper cites Scarselli, M.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Scarselli, M

Reference 32

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Observation 78376602-37ef-4061-bb18-e0c020c345f8 · outbound

This paper cites Helly, Joey Braspenning, Willem Elbers, Ian G.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Helly, Joey Braspenning, Willem Elbers, Ian G

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:03.447162Z

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Observation 86d8455b-9643-464b-975c-410fb64c8afe · outbound

This paper cites Spergel, N.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Spergel, N

Reference 34

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Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Unresolved cited work

Reference 35

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Observation b83e0c64-d15d-4c50-acdc-ef42ee2b4bf0 · outbound

This paper cites Return of frustratingly easy domain adaptation.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Return of frustratingly easy domain adaptation

Reference 36

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Observation 27b7e06c-8b62-40c2-8b1e-5bc4adf7c426 · outbound

This paper cites Vegetti, S.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Vegetti, S

Reference 37

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Observation 37f58df1-1579-4693-9fed-0a1778eaf662 · outbound

This paper cites Weaver, Sam E.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Weaver, Sam E

Reference 38

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Observation b020630d-82c3-485d-8d25-20359ed562b9 · outbound

This paper cites Wechsler and Jeremy L.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Wechsler and Jeremy L

Reference 39

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Observation a4d7b4c1-bb24-45af-95a8-5f4436ece931 · outbound

This paper cites Wu and Christian Kragh Jespersen.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Wu and Christian Kragh Jespersen

Reference 40

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Observation f7679856-16a4-4250-a6da-010dbc5082f9 · outbound

This paper cites Wu, Christian Kragh Jespersen, and Risa H.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Wu, Christian Kragh Jespersen, and Risa H

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:25:03.308862Z

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Observation c8530d07-bba1-4972-a8b6-b1cce27c8b96 · outbound

This paper cites Galaxy cluster mass estimation with deep learning and hydrodynamical simulations.

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Galaxy cluster mass estimation with deep learning and hydrodynamical simulations

Reference 42

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Pith citing papers

Observation 8885b588-3006-4432-b5e7-40608d9afc28 · inbound

Learning from galactic rotation curves: a neural network approach cites this paper.

Learning from galactic rotation curves: a neural network approach Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks

Reference 23

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Observation 92a6b3cf-576c-4bd9-8f18-3c0170dbf641 · inbound

Cluster Mass Inference from Galaxy Kinematics cites this paper.

Cluster Mass Inference from Galaxy Kinematics Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-06-27T07:30:41.906832Z

Source-reported events for the cited work

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