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

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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

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

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

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

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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

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

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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

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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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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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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

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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

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

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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

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

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

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

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

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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

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

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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

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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

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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

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

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

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

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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

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

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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

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

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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

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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

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

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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

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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

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

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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

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

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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

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

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

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

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

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

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

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

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

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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

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

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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

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-11T06:34:44.6726+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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

Resolution: verified exact; doi, observed 2026-08-05T11:41:23.893566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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

Resolution: 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 2026-08-11T06:34:44.6726+00:00.

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 2026-08-11T06:34:44.6726+00:00.

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

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-11T06:34:44.6726+00:00.

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: verified exact; doi, observed 2026-08-05T11:41:23.802135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.409852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.414830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.418914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.423195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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: verified exact; doi, observed 2026-08-05T11:41:23.755501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.431331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.435567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; doi, observed 2026-08-05T11:41:23.719901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.444356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.453396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.462460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; doi, observed 2026-08-05T11:41:23.673707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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; local_arxiv, observed 2026-08-05T11:41:24.525085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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: unresolved; no resolver link, observed 2026-08-05T11:41:23.475779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; no resolver link, observed 2026-08-05T11:41:23.480208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; no resolver link, observed 2026-08-05T11:41:23.484979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; no resolver link, observed 2026-08-05T11:41:23.489460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; doi, observed 2026-08-05T11:41:23.628730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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; doi, observed 2026-08-05T11:41:23.614039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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; no resolver link, observed 2026-08-05T11:41:23.501828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; no resolver link, observed 2026-08-05T11:41:23.506173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; local_arxiv, observed 2026-08-05T11:41:23.576923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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; doi, observed 2026-08-05T11:41:23.554436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Reference resolution

Outbound references

Pith citing papers