Paper Citation Record · LEDGER

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification

As of 19 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 2 inbound Pith citation observations for arXiv:2412.03029.

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

pith.paper-citation-record.v1
2412.03029 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

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measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:05:22.182974Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

54 of 54 outbound references displayed

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External citation measurements

1
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Outbound references

Observation 9f7da4fe-a8a0-40c4-8234-0bfe9313f0eb · outbound

This paper cites write newline.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification write newline

Reference 1

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Observation adcbd36e-823d-4d7f-bc20-66bc1ead37ea · outbound

This paper cites write newline.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification write newline

Reference 2

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Observation b1a543b9-0aa4-4b26-b16c-76243eed5053 · outbound

This paper cites an unresolved cited work.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 3

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Observation d5fbccc5-cd55-474e-8af5-8b7873346d67 · outbound

This paper cites D., D'Aloisio A., Christenson H.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification D., D'Aloisio A., Christenson H

Reference 4

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Observation dcaf1b2a-27e8-4f71-a440-c7d0d518d9f9 · outbound

This paper cites A., Xue X.-X., Liu C., Shen J., Flynn C., Yang C., Zhao G., Tian H.-J., 2021, @doi [ ] 10.3847/1538-4357/abfa9e , https://ui.adsabs.harvard.edu/abs/2021ApJ...919...66B 919, 66.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification A., Xue X.-X., Liu C., Shen J., Flynn C., Yang C., Zhao G., Tian H.-J., 2021, @doi [ ] 10.3847/1538-4357/abfa9e , https://ui.adsabs.harvard.edu/abs/2021ApJ...919...66B 919, 66

Reference 5

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Observation 5a00234e-3534-4d62-857a-0da44ef2f02f · outbound

This paper cites M., 2006, Pattern Recognition and Machine Learning.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification M., 2006, Pattern Recognition and Machine Learning

Reference 6

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Observation 63ea2ab7-ff04-485f-8821-ac836eab630a · outbound

This paper cites Constraints on the mean free path of ionising photons at $z\sim6$ using limits on individual free paths.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Constraints on the mean free path of ionising photons at $z\sim6$ using limits on individual free paths

Reference 7

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This paper cites W., Roweis S.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification W., Roweis S

Reference 8

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 9

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 10

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 11

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This paper cites Modeling the Gaia Color-Magnitude Diagram with Bayesian Neural Flows to Constrain Distance Estimates.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Modeling the Gaia Color-Magnitude Diagram with Bayesian Neural Flows to Constrain Distance Estimates

Reference 12

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This paper cites B., Bosman S.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification B., Bosman S

Reference 13

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 14

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This paper cites an unresolved cited work.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 15

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Observation 31f1f6c2-c7e0-4f1b-b46d-2bd6d05430f1 · outbound

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification A., Bovy J., Myers A

Reference 16

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Observation 9954e3dc-7ec2-4c09-bd80-919d76d4e0c2 · outbound

This paper cites Density Deconvolution with Normalizing Flows.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Density Deconvolution with Normalizing Flows

Reference 17

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This paper cites P., 2013, The Messenger, https://ui.adsabs.harvard.edu/abs/2013Msngr.154...32E 154, 32.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification P., 2013, The Messenger, https://ui.adsabs.harvard.edu/abs/2013Msngr.154...32E 154, 32

Reference 18

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 21

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 22

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Gradient-based training of Gaussian Mixture Models for High-Dimensional Streaming Data

Reference 23

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This paper cites R., et al., 2020, @doi [Nature] 10.1038/s41586-020-2649-2 , 585, 357.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification R., et al., 2020, @doi [Nature] 10.1038/s41586-020-2649-2 , 585, 357

Reference 24

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification pp 1026--1034, @doi 10.1109/ICCV.2015.123

Reference 25

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 26

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 27

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 29

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 30

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Variational Inference with Normalizing Flows

Reference 31

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Adam: A Method for Stochastic Optimization

Reference 33

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification M., Lang D., Schlafly E

Reference 37

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification J., Patel M., Warren S

Reference 38

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification J., et al., 2011b, @doi [ ] 10.1038/nature10159 , https://ui.adsabs.harvard.edu/abs/2011Natur.474..616M 474, 616

Reference 39

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification D., et al., 2015, @doi [The Astrophysical Journal Supplement Series] 10.1088/0067-0049/221/2/27 , 221, 27

Reference 40

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification F., Wang F., Yang J., Schindler J.-T., Fan X., 2022, @doi [ ] 10.1093/mnras/stac1944 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.515.3224N 515, 3224

Reference 41

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Curran Associates, Inc., pp 8024--8035, http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf

Reference 42

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Scalable Extreme Deconvolution

Reference 43

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification F., Meisner A

Reference 45

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification A., Carroll R

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification F., Davies F

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

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Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 55

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This paper cites G., et al., 2000, @doi [ ] 10.1086/301513 , https://ui.adsabs.harvard.edu/abs/2000AJ....120.1579Y 120, 1579.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification G., et al., 2000, @doi [ ] 10.1086/301513 , https://ui.adsabs.harvard.edu/abs/2000AJ....120.1579Y 120, 1579

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T22:55:54.085863Z

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Observation 9f3b4aa4-216d-4baf-80a0-5fb6946645fa · outbound

This paper cites an unresolved cited work.

Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification Unresolved cited work

Reference 57

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Observation 3d7e2e3b-5290-44ce-aeda-82f9bf047038 · inbound

Denoising Milky Way stellar survey data with normalizing flow models cites this paper.

Denoising Milky Way stellar survey data with normalizing flow models Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:05:22.182974Z

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Observation 734c80b9-6aae-4df7-96f3-ee6b36bc6fb0 · inbound

Using Neural Emulators and Hamiltonian Monte Carlo to constrain the Epoch of Reionization's History with the Ly$\alpha$ Forest Power Spectrum cites this paper.

Using Neural Emulators and Hamiltonian Monte Carlo to constrain the Epoch of Reionization's History with the Ly$\alpha$ Forest Power Spectrum Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification

Reference 66

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T16:39:59.719075Z

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