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Paper Citation Record · LEDGER

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study

As of 9 August 2026, this Paper Citation Record lists 95 of 95 outbound references and 1 inbound Pith citation observation for arXiv:2509.02414.

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

pith.paper-citation-record.v1
2509.02414 v1

Coverage vector

measured 95 of 95 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:41:23.514537Z

measured 96 of 96 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:40:13.554185Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-01T18:16:15.623592Z

Reference resolution

95 of 95 outbound references displayed

  • verified exact30
  • verified fuzzy0
  • unresolved65
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c3615376-665a-4791-9d15-6a0450de9ec5 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study , " * write output.state after.block = add.period write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a88579c6-ef09-4f31-a568-65394c323311 · outbound

This paper cites write newline.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study write newline

Reference 2

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Observation 2fe75f0f-09c2-45cf-af9f-0bcbbb21d89b · outbound

This paper cites 9#] <NM-.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 9#] <NM-

Reference 3

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Observation 092d8e20-873c-4f94-95d2-33c50185d807 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 4

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 75cac79e-adba-45b2-8337-bd959fa2c336 · outbound

This paper cites H., Hearin, A.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study H., Hearin, A

Reference 5

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Observation b2bba78d-6a6a-4f8d-a374-32da866e6769 · outbound

This paper cites L., Breysse, P.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study L., Breysse, P

Reference 6

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Observation 0e0c2307-558c-4950-889a-30a79d7f0bc5 · outbound

This paper cites L., Breysse, P.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study L., Breysse, P

Reference 7

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Observation aea26816-f126-448b-91a4-120686aef75c · outbound

This paper cites L., Caputo, A., & Kamionkowski, M.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study L., Caputo, A., & Kamionkowski, M

Reference 8

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Observation e9917922-fe1f-45b4-b7a4-736fc25f12c0 · outbound

This paper cites L., Caputo, A., Villaescusa-Navarro, F., & Kamionkowski, M.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study L., Caputo, A., Villaescusa-Navarro, F., & Kamionkowski, M

Reference 9

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verified exact
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Observation d83f7b02-1b41-448a-b55d-9266d1ec9a3a · outbound

This paper cites L., & Kovetz, E.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study L., & Kovetz, E

Reference 10

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Observation f0b53645-4e1e-4f03-90fe-1d78c98d0e62 · outbound

This paper cites 2022, title CONCERTO: High-fidelity simulation of millimeter line emissions of galaxies and [CII] intensity mapping , Astron.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2022, title CONCERTO: High-fidelity simulation of millimeter line emissions of galaxies and [CII] intensity mapping , Astron

Reference 11

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Observation 44abb64f-f719-4174-8ea0-6be6fd67298a · outbound

This paper cites C., & Alexandroff , R.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study C., & Alexandroff , R

Reference 12

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8686e01e-8034-4a31-9eec-477ac311f833 · outbound

This paper cites C., Kovetz, E.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study C., Kovetz, E

Reference 13

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Unavailable: canonical work link unavailable.

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Observation db810e11-cd2a-44c1-8a4d-f38a4d377636 · outbound

This paper cites C., & Rahman, M.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study C., & Rahman, M

Reference 14

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 24d74184-fba7-485b-94ab-f82a2b97820b · outbound

This paper cites C., et al.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study C., et al

Reference 15

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Observation 34e1a69e-7500-477f-9e2f-29859adf3b6f · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 16

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Unavailable: canonical work link unavailable.

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Observation cafdf140-3efb-4d9a-8163-3b27ef7fefac · outbound

This paper cites Correcting for interloper contamination in the power spectrum with neural networks.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Correcting for interloper contamination in the power spectrum with neural networks

Reference 17

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Observation 916be91a-320b-460e-a7d8-87adf8700a95 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 18

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Observation 88fa9243-994c-48b5-ab21-f5498b4362c5 · outbound

This paper cites Tomography of the Cosmic Dawn and Reionization Eras with Multiple Tracers.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Tomography of the Cosmic Dawn and Reionization Eras with Multiple Tracers

Reference 19

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Observation f1a57c21-3559-4a10-aa29-0a89e8c32203 · outbound

This paper cites B., Harker , G., et al.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study B., Harker , G., et al

Reference 20

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Observation 85c2b142-9a23-4ac9-91b8-1fe368deefcb · outbound

This paper cites C., et al.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study C., et al

Reference 21

Resolution
verified exact
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Observation ccbf52b4-5de1-47e7-a418-a268ec55716b · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 22

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Observation 45c186e7-e74d-426b-ab08-8c40da444e7d · outbound

This paper cites M., & Cooray , A.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study M., & Cooray , A

Reference 23

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Observation 725b2e8b-fd27-4f13-a5b7-cad1b34db030 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 24

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Observation 664a21e1-9bca-4d50-beca-fd5e509004d7 · outbound

This paper cites D., Chang, T.-C., & Dore, O.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study D., Chang, T.-C., & Dore, O

Reference 25

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verified exact
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Observation 99a67472-e374-4081-b821-ba26bb43f246 · outbound

This paper cites D., Chang, T.-C., & Dor \'e , O.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study D., Chang, T.-C., & Dor \'e , O

Reference 26

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Observation 969aacef-cd56-474c-be6b-2ea8a78e418e · outbound

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Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study A., et al

Reference 27

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Observation b22a33f4-c750-437d-a6bb-c7e86d45f505 · outbound

This paper cites 2016, title Probing high-redshift galaxies with Ly intensity mapping , Mon.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2016, title Probing high-redshift galaxies with Ly intensity mapping , Mon

Reference 28

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verified exact
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Source-reported events for the cited work

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Observation f29ffd81-c27b-45f1-9186-e36fbb024f1e · outbound

This paper cites 2016, title Observational challenges in Ly intensity mapping , Mon.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2016, title Observational challenges in Ly intensity mapping , Mon

Reference 29

Resolution
verified exact
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Source-reported events for the cited work

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Observation b41e3e2e-1a5f-4436-a6a0-56bd3fdb2037 · outbound

This paper cites 2020, title A wide field-of-view low-resolution spectrometer at APEX: Instrument design and scientific forecast , , 642, A60, 10.1051/0004-6361/202038456.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2020, title A wide field-of-view low-resolution spectrometer at APEX: Instrument design and scientific forecast , , 642, A60, 10.1051/0004-6361/202038456

Reference 30

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Observation b03b97e6-4af9-4923-a217-9e236d09de1f · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 31

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Unavailable: canonical work link unavailable.

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Observation 9929ab5c-3f68-4f36-9980-b736b4a62a40 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 32

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3f049020-8fc4-4b89-8a98-45605a6337d5 · outbound

This paper cites Cosmic Dawn Intensity Mapper.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Cosmic Dawn Intensity Mapper

Reference 33

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c79a6d3b-36c2-4d25-bda6-35bbe28c184a · outbound

This paper cites 2018, title Searching for Decaying and Annihilating Dark Matter with Line Intensity Mapping , Phys.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2018, title Searching for Decaying and Annihilating Dark Matter with Line Intensity Mapping , Phys

Reference 34

Resolution
verified exact
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Source-reported events for the cited work

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Observation e8cd171a-fbe1-4ded-882a-50a6f32cd437 · outbound

This paper cites T., Bock , J.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study T., Bock , J

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e5854f59-d68a-4aa1-bb0c-6170e5d02ede · outbound

This paper cites 2021, title Microwave spectro-polarimetry of matter and radiation across space and time , Exper.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2021, title Microwave spectro-polarimetry of matter and radiation across space and time , Exper

Reference 36

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Observation 9f52cb61-7091-4cc8-aacd-4c5d6319615e · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 37

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Observation 8f355a22-015c-44ca-99d9-09f7d923ca12 · outbound

This paper cites Science Impacts of the SPHEREx All-Sky Optical to Near-Infrared Spectral Survey II: Report of a Community Workshop on the Scientific Synergies Between the SPHEREx Survey and Other Astronomy Observatories.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Science Impacts of the SPHEREx All-Sky Optical to Near-Infrared Spectral Survey II: Report of a Community Workshop on the Scientific Synergies Between the SPHEREx Survey and Other Astronomy Observatories

Reference 38

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no resolver link, observed 2026-08-05T11:41:20.201195Z

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source=arxiv_source observed=2026-08-05T11:41:20.201195Z digest=sha256:c843d2ebfa1cbbfb241a93c9f1ac48b3b814c94322640783f9bddcbca448716c

Observation 5f1a07bd-8101-4f23-b01b-3aaf14b287ea · outbound

This paper cites CIBER 4th flight fluctuation analysis: Measurements of near-IR auto- and cross-power spectra on arcminute to sub-degree scales.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study CIBER 4th flight fluctuation analysis: Measurements of near-IR auto- and cross-power spectra on arcminute to sub-degree scales

Reference 39

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source=arxiv_source observed=2026-08-05T11:41:20.308013Z digest=sha256:ce14d676900b4929d9f055bd93a86db422d4fe1f07d8ef1503cbd79985729205

Observation e7046b92-74da-4708-a491-df6ce516ada1 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 40

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no resolver link, observed 2026-08-05T11:41:20.389577Z

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source=arxiv_source observed=2026-08-05T11:41:20.389577Z digest=sha256:80137b71a3f52feb2821cb9b031c7547b5a1d2c3d406c2242d712745b9c05fcb

Observation d54d77c8-67b3-4a71-b05f-2f9dd42eae3d · outbound

This paper cites 2021, title The Hobby Eberly Telescope Dark Energy Experiment (HETDEX) Survey Design, Reductions, and Detections* , Astrophys.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2021, title The Hobby Eberly Telescope Dark Energy Experiment (HETDEX) Survey Design, Reductions, and Detections* , Astrophys

Reference 41

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no resolver link, observed 2026-08-05T11:41:20.497911Z

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source=arxiv_source observed=2026-08-05T11:41:20.497911Z digest=sha256:f973839118460b84a4c500ceba2d52383553c7196753c33685e2c3f0787c4817

Observation 8bbefc29-f738-481f-917a-e09db6f5a334 · outbound

This paper cites 2012, title Intensity Mapping of the [C II] Fine Structure Line during the Epoch of Reionization , , 745, 49, 10.1088/0004-637X/745/1/49.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2012, title Intensity Mapping of the [C II] Fine Structure Line during the Epoch of Reionization , , 745, 49, 10.1088/0004-637X/745/1/49

Reference 42

Resolution
verified exact
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:20.672664Z digest=sha256:949a35c2a980018b63078eb8f8ac435bd15b4385add65320fc852cbe509178f8

Observation d1a78a06-2ecb-4957-84b9-4a98183833e8 · outbound

This paper cites B., et al.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study B., et al

Reference 43

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no resolver link, observed 2026-08-05T11:41:20.747823Z

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source=arxiv_source observed=2026-08-05T11:41:20.747823Z digest=sha256:213d6bacca6e012fa2ab0f8a6ad359c1c9a41642160bae5e073bd7c0f2f70593

Observation 9044875b-a362-4ea5-afea-b3ca33873da7 · outbound

This paper cites Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks

Reference 44

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source=arxiv_source observed=2026-08-05T11:41:20.826035Z digest=sha256:9c6f6e8feccba746accc052d89dd1f3e7c23729d3dd57cbe7f679a536fb8be53

Observation 17730e67-56ef-4bd5-aaec-58fc52f62db9 · outbound

This paper cites S., & Bird, S.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study S., & Bird, S

Reference 45

Resolution
verified exact
doi, observed 2026-08-05T11:41:24.059098Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:20.934772Z digest=sha256:4096ecf26a2650f9325d55e3fb0189962433b16a246d0da96cc77d2054f2b835

Observation ed7f292c-d8af-43a0-87c9-f38e01dac9e0 · outbound

This paper cites Snowmass 2021 Cosmic Frontier White Paper: Cosmology with Millimeter-Wave Line Intensity Mapping.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Snowmass 2021 Cosmic Frontier White Paper: Cosmology with Millimeter-Wave Line Intensity Mapping

Reference 46

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no resolver link, observed 2026-08-05T11:41:21.042741Z

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source=arxiv_source observed=2026-08-05T11:41:21.042741Z digest=sha256:2c70673bc0d0b4711bd8412bf7703f6ddd56ccc3c869c37290e36ff9c5e1eca7

Observation 32d2d9d3-bd8c-495f-8b84-b20ae3c234aa · outbound

This paper cites S., et al.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study S., et al

Reference 47

Resolution
verified exact
doi, observed 2026-08-05T11:41:24.044180Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:21.146793Z digest=sha256:e5acdc3422b2144ad23d8887395b8f56e2dbbd767bca4d22e77f3e92bbc19866

Observation 8cf0bfd5-b377-46ea-aafd-499c0d06568d · outbound

This paper cites K., Marrone, D.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study K., Marrone, D

Reference 48

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no resolver link, observed 2026-08-05T11:41:21.222787Z

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source=arxiv_source observed=2026-08-05T11:41:21.222787Z digest=sha256:46303e69c1466206cc7f5f229bf2e0e45ca0950806a8af00c218b9920b8a7798

Observation 5424fce2-58b6-4db4-993d-9b811073decf · outbound

This paper cites K., Marrone, D.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study K., Marrone, D

Reference 49

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no resolver link, observed 2026-08-05T11:41:21.294741Z

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source=arxiv_source observed=2026-08-05T11:41:21.294741Z digest=sha256:f25ee3776d029c68095b8039188d6da03c828d56f51c6918539374eefd2b880a

Observation 8e62b286-8d2c-4f8b-a8dc-413b2d45c6e3 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Adam: A Method for Stochastic Optimization

Reference 50

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no resolver link, observed 2026-08-05T11:41:21.356376Z

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source=arxiv_source observed=2026-08-05T11:41:21.356376Z digest=sha256:54b3084417d236e46c14afb92d6e37869b7c2a8d190606b64482cccde839f102

Observation f3ec5592-34be-4735-93ca-385984d9f7ed · outbound

This paper cites Astrophysics and Cosmology with Line-Intensity Mapping.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Astrophysics and Cosmology with Line-Intensity Mapping

Reference 51

Resolution
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no resolver link, observed 2026-08-05T11:41:21.440287Z

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source=arxiv_source observed=2026-08-05T11:41:21.440287Z digest=sha256:b1111048d3617853a394ffeb05d8ccad66ab03178c889d43dc77f06e6cb00bc7

Observation 1bcfb617-ea3f-4ee1-bf82-71e2dd09ca11 · outbound

This paper cites Line-Intensity Mapping: 2017 Status Report.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Line-Intensity Mapping: 2017 Status Report

Reference 52

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no resolver link, observed 2026-08-05T11:41:21.608655Z

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source=arxiv_source observed=2026-08-05T11:41:21.608655Z digest=sha256:f6279d40fd9e1442ea0d56be423953e95b37ac5c48059599f0f7bd0e57f9c647

Observation eaf2f92b-80e0-4e38-a84b-95a9be1d1e24 · outbound

This paper cites in prep., title Euclid preparation.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study in prep., title Euclid preparation

Reference 53

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no resolver link, observed 2026-08-05T11:41:21.693456Z

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source=arxiv_source observed=2026-08-05T11:41:21.693456Z digest=sha256:be51e865372296ca97275be0328f56d8525e29161f627e08f4ae43a6e32626d6

Observation 6dfc51db-fa9f-434c-b44d-bce4e21604c4 · outbound

This paper cites Y., Wechsler, R.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Y., Wechsler, R

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-05T11:41:21.775207Z

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source=arxiv_source observed=2026-08-05T11:41:21.775207Z digest=sha256:ad2d1bf2801dfaf29934515e0135ec8d29993b857011d43382da5f51a96b013b

Observation e53e6e61-d941-486b-99ea-97c3be07446f · outbound

This paper cites 2016, title On Removing Interloper Contamination from Intensity Mapping Power Spectrum Measurements , , 825, 143, 10.3847/0004-637X/825/2/143.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2016, title On Removing Interloper Contamination from Intensity Mapping Power Spectrum Measurements , , 825, 143, 10.3847/0004-637X/825/2/143

Reference 55

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no resolver link, observed 2026-08-05T11:41:21.881542Z

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source=arxiv_source observed=2026-08-05T11:41:21.881542Z digest=sha256:bbc204770fe6b23c769f2c0d27a42694ba3bd9e63c11d39f84b583b5119fd7b1

Observation eb84e429-36c2-4492-9834-f8a94f384f27 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 56

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unresolved
no resolver link, observed 2026-08-05T11:41:21.986490Z

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source=arxiv_source observed=2026-08-05T11:41:21.986490Z digest=sha256:43e90b0e90c644b3039901e47abe0489be75c18fd340d883784e6aa6a15bdff8

Observation 917acd05-ff86-4003-9d39-ff935ca2a4cf · outbound

This paper cites 2011, title A method for 21 cm power spectrum estimation in the presence of foregrounds , , 83, 103006, 10.1103/PhysRevD.83.103006.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2011, title A method for 21 cm power spectrum estimation in the presence of foregrounds , , 83, 103006, 10.1103/PhysRevD.83.103006

Reference 57

Resolution
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no resolver link, observed 2026-08-05T11:41:22.058202Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:41:22.058202Z digest=sha256:6d0ba1dd6bc0a95a4251a9628210ae71536709c6b9a6c785ca81b0004c4b937a

Observation 11d1a280-c4e5-4d61-9820-a4b6c08decab · outbound

This paper cites 2009, title An improved method for 21-cm foreground removal , , 398, 401, 10.1111/j.1365-2966.2009.15156.x.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2009, title An improved method for 21-cm foreground removal , , 398, 401, 10.1111/j.1365-2966.2009.15156.x

Reference 58

Resolution
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no resolver link, observed 2026-08-05T11:41:22.134694Z

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source=arxiv_source observed=2026-08-05T11:41:22.134694Z digest=sha256:7c13963d31556acbceac7290befa618d7f866a1d963700cf674e8bd0fefe8a22

Observation a93860b1-8bb9-452d-909a-15d40da2afab · outbound

This paper cites 2013, title A comparison of approaches in fitting continuum SEDs , Research in Astronomy and Astrophysics, 13, 420, 10.1088/1674-4527/13/4/005.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2013, title A comparison of approaches in fitting continuum SEDs , Research in Astronomy and Astrophysics, 13, 420, 10.1088/1674-4527/13/4/005

Reference 59

Resolution
verified exact
doi, observed 2026-08-05T11:41:23.949639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:22.168479Z digest=sha256:f69ff5dd2aaf1354d95b6cbbf688ba0170ef8a153b670ec02bc0a507410a62dc

Observation 40efab1b-8d05-4cb3-af9d-3be57642cb3b · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 60

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unresolved
no resolver link, observed 2026-08-05T11:41:22.209004Z

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source=arxiv_source observed=2026-08-05T11:41:22.209004Z digest=sha256:222637c73f76d386947a68758e17eaec4cecd0af42085eb6ad5b6fcce20b31f8

Observation bf628486-c35e-4f79-b5b8-b2e964e63f13 · outbound

This paper cites 2015, title Predicting the intensity mapping signal for multi-J CO lines , , 2015, 028, 10.1088/1475-7516/2015/11/028.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2015, title Predicting the intensity mapping signal for multi-J CO lines , , 2015, 028, 10.1088/1475-7516/2015/11/028

Reference 61

Resolution
verified exact
doi, observed 2026-08-05T11:41:23.935035Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:22.281335Z digest=sha256:a8469ed188c290b235acf2506d9f74d143d47f88b0c7743dac07b34ab1fb4d38

Observation 910477ca-9925-466b-a6e0-287490ae08f7 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 62

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unresolved
no resolver link, observed 2026-08-05T11:41:22.329968Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:41:22.329968Z digest=sha256:ef90c8d66123667c5f6d5d924780ba855dfbf7f46afcaf5d088abee45449399c

Observation 120e1bae-25c0-419d-87dd-8cd30107abd8 · outbound

This paper cites 2019, title Intensity mapping with neutral hydrogen and the Hidden Valley simulations, Journal of Cosmology and Astroparticle Physics, 2019, 024–024, 10.1088/1475-7516/2019/09/024.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2019, title Intensity mapping with neutral hydrogen and the Hidden Valley simulations, Journal of Cosmology and Astroparticle Physics, 2019, 024–024, 10.1088/1475-7516/2019/09/024

Reference 63

Resolution
verified exact
doi, observed 2026-08-05T11:41:23.910568Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:22.410704Z digest=sha256:6f6e3ed80f0ad3e443c47f27f0c3aa005f0b972d6a5f403a9cb7afa0b4cdfcd2

Observation c87abb53-36fe-470a-bec4-ab6e77d96e01 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 64

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verified exact
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:22.540692Z digest=sha256:593cd300eda84291df06df3759def4a9098576075d60b65b4605be90d053712e

Observation d64743db-7225-427b-b1a4-aab376f4fa6b · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 65

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verified exact
doi, observed 2026-08-05T11:41:23.878936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:22.679374Z digest=sha256:8a73ce44a182ed3df57fda3d047a3806212a56ebc99d259bbf04fda58019a4a5

Observation 9ca6db3c-40d2-4782-9ba3-f0ddedc803f0 · outbound

This paper cites K., & Fialkov, A.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study K., & Fialkov, A

Reference 66

Resolution
verified exact
doi, observed 2026-08-05T11:41:23.863886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:22.790240Z digest=sha256:bbbb444474c93c939573a0ecd48d0109b2d9670ca35f5e164c5641dda4bea7be

Observation d7e93b0e-b7ee-439b-93a3-b380a66ae610 · outbound

This paper cites K., Karkare, K.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study K., Karkare, K

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-05T11:41:22.895577Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-05T11:41:22.895577Z digest=sha256:992a3ceacd31d7b1be38e5165b7cb050d1c604693b8cde3272cf612f17cda3ae

Observation 186c312c-6f1f-4496-8002-95d76f304eac · outbound

This paper cites K., & Castorina, E.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study K., & Castorina, E

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-05T11:41:23.062009Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:41:23.062009Z digest=sha256:823f556ec8bb6a88878255bf3017b27078aff84a32e5cad3bed880a92608a2e3

Observation 035a9bc4-08b4-4b42-9c8c-a69d66bea587 · outbound

This paper cites P., & Mack , K.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study P., & Mack , K

Reference 69

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unresolved
no resolver link, observed 2026-08-05T11:41:23.184400Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:41:23.184400Z digest=sha256:17d290c2bb2176e96e30f0f03fd05a3fe46a746dcf31ce6367a31d62b1d13dfe

Observation 449551b4-05cb-4b47-8bf8-820da8ea2872 · outbound

This paper cites R., & Loeb, A.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study R., & Loeb, A

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-05T11:41:23.296522Z

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source=arxiv_source observed=2026-08-05T11:41:23.296522Z digest=sha256:36900b08737fb7552c1e6e4c325d10343c74d77073ccc5aa142f522ea7c7b614

Observation 60c7af00-0d3e-4c9d-9422-2257b28259db · outbound

This paper cites R., Chang , T.-C., Dor \'e , O., & Lidz , A.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study R., Chang , T.-C., Dor \'e , O., & Lidz , A

Reference 71

Resolution
verified exact
doi, observed 2026-08-05T11:41:23.816497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1a560687-7bf5-48b4-b199-73a60f104dea · outbound

This paper cites R., Dore, O., & Bock, J.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study R., Dore, O., & Bock, J

Reference 72

Resolution
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Observation 3e7df3e1-1a8f-4ecf-948d-d7156f24625b · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 73

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f37a3871-361f-492e-8338-dffa15ac1817 · outbound

This paper cites 2025, title Euclid preparation.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2025, title Euclid preparation

Reference 74

Resolution
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Unavailable: canonical work link unavailable.

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Observation acaa7993-f63a-4bec-8f1e-e87df23dcea0 · outbound

This paper cites 2024, title Cross-correlation Techniques to Mitigate the Interloper Contamination for Line Intensity Mapping Experiments , Astrophys.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2024, title Cross-correlation Techniques to Mitigate the Interloper Contamination for Line Intensity Mapping Experiments , Astrophys

Reference 75

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6d9a508b-2472-4011-9280-ebbed5820a90 · outbound

This paper cites G., Cooray , A., & Knox , L.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study G., Cooray , A., & Knox , L

Reference 76

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d614fddf-1ab4-443a-adfb-d4b2e8ba2928 · outbound

This paper cites L., Kovetz, E.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study L., Kovetz, E

Reference 77

Resolution
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Observation ab9edc29-622a-4889-a3db-973b2617adb0 · outbound

This paper cites 2021 a , title Multi-tracer intensity mapping: Cross-correlations, Line noise & Decorrelation , JCAP, 05, 068, 10.1088/1475-7516/2021/05/068.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2021 a , title Multi-tracer intensity mapping: Cross-correlations, Line noise & Decorrelation , JCAP, 05, 068, 10.1088/1475-7516/2021/05/068

Reference 78

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 744ea7f5-4941-4693-9c9d-fc6e92d259b8 · outbound

This paper cites 2021 b , title Astrophysics & Cosmology from Line Intensity Mapping vs Galaxy Surveys , JCAP, 05, 067, 10.1088/1475-7516/2021/05/067.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2021 b , title Astrophysics & Cosmology from Line Intensity Mapping vs Galaxy Surveys , JCAP, 05, 067, 10.1088/1475-7516/2021/05/067

Reference 79

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f798d418-3679-43e3-b002-028243ef4678 · outbound

This paper cites R., Karkare, K.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study R., Karkare, K

Reference 80

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1e9d8346-820f-4c23-b99d-0b45c2a89e25 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 81

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ef36c3f9-1bd5-4276-a2f5-801a8539f20c · outbound

This paper cites B., Santos, M.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study B., Santos, M

Reference 83

Resolution
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Source-reported events for the cited work

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Observation a331c6ce-94f7-4f8d-866b-adf9968e86aa · outbound

This paper cites B., Santos , M.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study B., Santos , M

Reference 85

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2d58e14f-7a4d-471b-a688-7786b2bd45a5 · outbound

This paper cites B., Kovetz, E.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study B., Kovetz, E

Reference 86

Resolution
verified exact
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Source-reported events for the cited work

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Observation 17e71885-6830-41a3-b1fa-75e697d88b92 · outbound

This paper cites Cosmological Constraints on the Global Star Formation Law of Galaxies: Insights From Baryon Acoustic Oscillation Intensity Mapping.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Cosmological Constraints on the Global Star Formation Law of Galaxies: Insights From Baryon Acoustic Oscillation Intensity Mapping

Reference 87

Resolution
verified exact
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Source-reported events for the cited work

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Observation 1d9428cb-0022-40c1-aff2-aa676cb6c89c · outbound

This paper cites P., et al.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study P., et al

Reference 88

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a50ec246-70d5-4442-a254-d78769660fe6 · outbound

This paper cites 2023, title CONCERTO: Extracting the power spectrum of the [C II ] emission line , Astron.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2023, title CONCERTO: Extracting the power spectrum of the [C II ] emission line , Astron

Reference 89

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bd4691f6-02f0-4f24-9226-8ce98e4ead36 · outbound

This paper cites The Terahertz Intensity Mapper (TIM): a Next-Generation Experiment for Galaxy Evolution Studies.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study The Terahertz Intensity Mapper (TIM): a Next-Generation Experiment for Galaxy Evolution Studies

Reference 90

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a0eaba13-3398-4d75-bdad-269cdf811141 · outbound

This paper cites 2022, title The CAMELS Multifield Data Set: Learning the Universe s Fundamental Parameters with Artificial Intelligence , Astrophys.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2022, title The CAMELS Multifield Data Set: Learning the Universe s Fundamental Parameters with Artificial Intelligence , Astrophys

Reference 91

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 35ce19c7-cf16-4a75-85c8-a0d8336f9e17 · outbound

This paper cites an unresolved cited work.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Unresolved cited work

Reference 92

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1c3f2d43-9303-4e76-ad23-033e92373b41 · outbound

This paper cites R., & Switzer, E.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study R., & Switzer, E

Reference 93

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3677ada5-fecf-404c-86ad-7824b8118f3a · outbound

This paper cites 2015, title Intensity mapping of [C II] emission from early galaxies , Mon.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2015, title Intensity mapping of [C II] emission from early galaxies , Mon

Reference 94

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 27c2f935-6611-4f6f-b733-28ec8354ea58 · outbound

This paper cites R., & Hernquist , L.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study R., & Hernquist , L

Reference 95

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:41:23.506173Z digest=sha256:83140006a3574f4372a0336b5cb9512d03caecf1a364fe65865fbae9ffecdafe

Observation 5e19fc16-b26c-463e-a77c-ffef7a543889 · outbound

This paper cites Robust Intensity Mapping Analysis against Foregrounds for the Epoch of Reionization.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study Robust Intensity Mapping Analysis against Foregrounds for the Epoch of Reionization

Reference 96

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T11:41:23.510337Z digest=sha256:a98b814ba7881956924ef10149b3d89f7719ad673eb796f83a9995f962d7cc68

Observation 3de5f2cc-50b9-4dde-9bbc-9055ba297635 · outbound

This paper cites 2021, title Antisymmetric Cross-correlation between H I and CO Line Intensity Maps as a New Probe of Cosmic Reionization , Astrophys.

Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study 2021, title Antisymmetric Cross-correlation between H I and CO Line Intensity Maps as a New Probe of Cosmic Reionization , Astrophys

Reference 97

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Pith citing papers

Observation e90107f6-93ad-4ac3-b14f-3494788afb67 · inbound

Reading Between the Lines: Forward Modeling Dust, Continuum, and Spectral Cleaning for Multi-Line Intensity Mapping cites this paper.

Reading Between the Lines: Forward Modeling Dust, Continuum, and Spectral Cleaning for Multi-Line Intensity Mapping Disentangling Target Lines from Interlopers and Continuum with Neural Networks: A SPHEREx Intensity Mapping Case Study

Reference 195

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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