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Paper Citation Record · LEDGER

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time

As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.18311.

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

pith.paper-citation-record.v1
2505.18311 v2

Coverage vector

measured 39 of 39 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation f4626975-c146-4419-b0c6-1d1459ac1180 · outbound

This paper cites Figure 7 shows the NN interval width with 96% target accuracy.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Figure 7 shows the NN interval width with 96% target accuracy

Reference 1

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Observation c54e3230-1cfb-4069-bd34-d4aaf7bac7e4 · outbound

This paper cites an unresolved cited work.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Unresolved cited work

Reference 2

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Observation 41596725-d384-461f-bb03-f6ed3c2061f9 · outbound

This paper cites Abbott et al.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Abbott et al

Reference 3

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Observation a9ae652d-9327-4eda-8879-14ec8c8047cd · outbound

This paper cites GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run

Reference 4

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Observation fe8800a3-e69f-42b2-803b-0f350924254b · outbound

This paper cites an unresolved cited work.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Unresolved cited work

Reference 5

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Observation 3b78ed8f-9599-4d79-89e8-857e38eafb05 · outbound

This paper cites an unresolved cited work.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Unresolved cited work

Reference 6

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Observation b48fad23-5fa7-4a7c-b957-8f9d3d2dd59f · outbound

This paper cites Performance of the low-latency GstLAL inspiral search towards LIGO, Virgo, and KAGRA's fourth observing run.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Performance of the low-latency GstLAL inspiral search towards LIGO, Virgo, and KAGRA's fourth observing run

Reference 7

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Observation 65492cd8-6ff4-4bed-a1dc-52dc6a8aad03 · outbound

This paper cites Realtime search for compact binary mergers in Advanced LIGO and Virgo's third observing run using PyCBC Live.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Realtime search for compact binary mergers in Advanced LIGO and Virgo's third observing run using PyCBC Live

Reference 8

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Observation 3f3eef28-9477-4cdb-b7c1-78ca23173ee5 · outbound

This paper cites The MBTA Pipeline for Detecting Compact Binary Coalescences in the Third LIGO-Virgo Observing Run.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time The MBTA Pipeline for Detecting Compact Binary Coalescences in the Third LIGO-Virgo Observing Run

Reference 9

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Observation 9b291292-22cb-4a75-a390-37888b27c9fe · outbound

This paper cites The SPIIR online coherent pipeline to search for gravitational waves from compact binary coalescences.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time The SPIIR online coherent pipeline to search for gravitational waves from compact binary coalescences

Reference 10

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Observation ed204573-e5e5-4ed0-b3d3-9e349a20ef8b · outbound

This paper cites Sharma Chaudhary et al., Proceedings of the Na- tional Academy of Sciences 121, e2316474121 (2024), https://www.pnas.org/doi/pdf/10.1073/pnas.2316474121.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Sharma Chaudhary et al., Proceedings of the Na- tional Academy of Sciences 121, e2316474121 (2024), https://www.pnas.org/doi/pdf/10.1073/pnas.2316474121

Reference 11

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Observation cb194b0a-6da7-4da2-89b6-65a82b76f6fb · outbound

This paper cites Allen, W.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Allen, W

Reference 12

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Observation bda2e040-1e7c-4939-9192-181b99eb388b · outbound

This paper cites Cannon, R.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Cannon, R

Reference 13

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Observation 790ccdbe-eeb9-4715-8f91-57be50f28442 · outbound

This paper cites Template bank for compact binary mergers in the fourth observing run of Advanced LIGO, Advanced Virgo, and KAGRA.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Template bank for compact binary mergers in the fourth observing run of Advanced LIGO, Advanced Virgo, and KAGRA

Reference 14

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Observation c30db7e9-e202-4b57-9c3a-62f144be5a1b · outbound

This paper cites Analysis Framework for the Prompt Discovery of Compact Binary Mergers in Gravitational-wave Data.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Analysis Framework for the Prompt Discovery of Compact Binary Mergers in Gravitational-wave Data

Reference 15

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Observation e6d852e5-7bbd-4551-b209-30e2cee3e3ba · outbound

This paper cites Improved ranking statistics of the GstLAL inspiral search for compact binary coalescences.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Improved ranking statistics of the GstLAL inspiral search for compact binary coalescences

Reference 16

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Observation 677b2fd6-f13c-46c1-b739-7c1ba6372cd9 · outbound

This paper cites Chatterjee, S.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Chatterjee, S

Reference 17

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Observation c7e5f562-bf5d-4ae2-8a65-c9ec6a3ad5e3 · outbound

This paper cites Baird, S.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Baird, S

Reference 18

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Observation 0ecb3f77-edb8-4862-9858-e5e069792c6a · outbound

This paper cites Capano, I.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Capano, I

Reference 19

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Observation 057afb09-363d-4548-bf75-4b7a5a830935 · outbound

This paper cites Margalit and B.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Margalit and B

Reference 20

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Observation 4016ea0b-3bf2-46a5-a570-cda9936c1431 · outbound

This paper cites Berbel, M.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Berbel, M

Reference 21

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Observation aaada7f0-3ae2-4d4f-a0a3-8f3001348468 · outbound

This paper cites Bassett, Jr., and R.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Bassett, Jr., and R

Reference 22

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Observation 590fb48f-cea0-41e5-874d-5814e003c846 · outbound

This paper cites thesis, University of Wisconsin-Milwaukee (2024).

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time thesis, University of Wisconsin-Milwaukee (2024)

Reference 25

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A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Unresolved cited work

Reference 26

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A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Unresolved cited work

Reference 27

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A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Unresolved cited work

Reference 28

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Observation ca13268e-8590-44e7-9ba7-0b9b3c541af7 · outbound

This paper cites PyTorch documentation,.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time PyTorch documentation,

Reference 29

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Observation caba3924-89c9-4d08-ae2b-06eb4fd7d171 · outbound

This paper cites Rectifier nonlinearities improve neural net- work acoustic models,.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Rectifier nonlinearities improve neural net- work acoustic models,

Reference 30

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Observation 5a6c0e16-5402-4b62-b76f-306d16017a03 · outbound

This paper cites Blondel, O.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Blondel, O

Reference 31

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Observation c6e7b027-3d5d-4800-b714-4981bd3d98f6 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Adam: A Method for Stochastic Optimization

Reference 32

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Observation 1d9e1ab4-9fe0-4c4d-b455-2e2ae7d030ff · outbound

This paper cites GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run

Reference 33

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Observation ac98dca9-c274-4cbf-b45c-6ab23980ac42 · outbound

This paper cites Ashton, M.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Ashton, M

Reference 34

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Observation b54a8ad4-92e9-4758-b9e6-0370f4914613 · outbound

This paper cites dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences

Reference 35

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Observation 0b80e0a0-0381-4eb0-ad3a-d12c905da305 · outbound

This paper cites Accelerated gravitational-wave parameter estimation with reduced order modeling.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Accelerated gravitational-wave parameter estimation with reduced order modeling

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Observation cea9bf56-a3ad-42ff-aa49-2e03edc7cf4e · outbound

This paper cites Fast and Accurate Inference on Gravitational Waves from Precessing Compact Binaries.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Fast and Accurate Inference on Gravitational Waves from Precessing Compact Binaries

Reference 37

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source=pdf_text observed=2026-08-07T14:37:51.242324Z digest=sha256:53544a9695955be0fc52b5faf08529fd2a97aa32fd3be860a47a078cd0ca6fe0

Observation 637d27dc-4a64-4c87-b2b1-3defad6cbaaf · outbound

This paper cites Morisaki, R.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Morisaki, R

Reference 38

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Observation b783c1ab-365d-4bdb-9bb0-79d3a1feb064 · outbound

This paper cites Accelerated parameter estimation in Bilby with relative binning.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Accelerated parameter estimation in Bilby with relative binning

Reference 39

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source=pdf_text observed=2026-08-07T14:37:51.438848Z digest=sha256:4dec73bcf3d6a5559d3044b100c339e821ac267da245968e9f7339b9ed235fff

Observation a252d61e-ebfe-462b-8e7a-8681cbf09df8 · outbound

This paper cites Pankow, P.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Pankow, P

Reference 40

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raw_fallback, observed 2026-08-07T14:37:52.555837Z

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Observation 6c44a336-c9a9-41ae-9b75-f1f05cea6c3d · outbound

This paper cites Supplementing rapid Bayesian parameter estimation schemes with adaptive grids.

A neural network for estimating compact binary coalescence parameters of gravitational-wave events in real time Supplementing rapid Bayesian parameter estimation schemes with adaptive grids

Reference 41

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source=pdf_text observed=2026-08-07T14:37:51.646771Z digest=sha256:44e8bf1215d135840e5e04622bbbe07de1680da5b13ed63c81b901bd22d5a161

Pith citing papers

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