Paper Citation Record · LEDGER

Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2407.14298.

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pith.paper-citation-record.v1
2407.14298 v2

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measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:41:41.420806Z

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

Source: arxiv_reference, observed 2026-05-21T03:33:56.396686Z

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Pith citing papers

Observation 6956d4d0-15a0-4523-bbb3-2f383ebea67e · inbound

Analytical modeling of the one-dimensional power spectrum of 21-cm forest based on a halo model method cites this paper.

Analytical modeling of the one-dimensional power spectrum of 21-cm forest based on a halo model method Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 93

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Source-reported events for the cited work

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Observation 34a12bc9-7340-43de-85a9-a38555598e39 · inbound

Prospects of a statistical detection of the 21-cm forest and its potential to constrain the thermal state of the neutral IGM during reionization cites this paper.

Prospects of a statistical detection of the 21-cm forest and its potential to constrain the thermal state of the neutral IGM during reionization Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-11T19:26:46.146417Z

Source-reported events for the cited work

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Observation 703432a2-f277-4430-90b9-e40e703d3668 · inbound

Prospects for measuring neutrino mass with 21-cm forest cites this paper.

Prospects for measuring neutrino mass with 21-cm forest Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-10T22:48:21.459484Z

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Observation a22ba01b-a7c4-4789-8af2-e9362a966c5c · inbound

Configuration Requirements for 21-cm Forest Background Quasar Searches with the Moon-based Interferometer cites this paper.

Configuration Requirements for 21-cm Forest Background Quasar Searches with the Moon-based Interferometer Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T11:41:41.420806Z

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Observation bb7b9dd7-f68d-4d46-ab83-1ab55d7c8aad · inbound

Parameter inference of millilensed gravitational waves using neural spline flows cites this paper.

Parameter inference of millilensed gravitational waves using neural spline flows Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-19T13:22:18.832637Z

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Observation 208fc511-4827-41aa-9b7e-1ae58d2ddd7d · inbound

Probing initial isocurvature perturbation with 21cm one-point statistics cites this paper.

Probing initial isocurvature perturbation with 21cm one-point statistics Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-04T16:19:49.916330Z

Source-reported events for the cited work

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Observation ed65552e-9946-4826-b1a1-14cb3123222f · inbound

Topological Signatures of Heating and Dark Matter in the 21 cm Forest cites this paper.

Topological Signatures of Heating and Dark Matter in the 21 cm Forest Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-17T21:20:16.914981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5c017b17-8448-4d63-96a6-1005e87b8566 · inbound

Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows cites this paper.

Robust parameter inference for Taiji via time-frequency contrastive learning and normalizing flows Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:45:24.084359Z

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Observation 4bcec3cc-fd41-43f6-b0a9-a9c51dc8073e · inbound

Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection cites this paper.

Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 136

Resolution: verified exact; arxiv_id, observed 2026-05-21T03:33:56.398180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6bd77c41-1819-4140-854d-431ab6542bc9 · inbound

Identifying lensed gravitational waves with physics-informed posterior learning cites this paper.

Identifying lensed gravitational waves with physics-informed posterior learning Deep learning-driven likelihood-free parameter inference for 21-cm forest observations

Reference 163

Resolution: unresolved; no resolver link, observed 2026-07-11T23:16:00.672720Z

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Unavailable: canonical work link unavailable.