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Paper Citation Record · LEDGER

A comparative study of cosmological constraints from weak lensing using Convolutional Neural Networks

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.03490.

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

pith.paper-citation-record.v1
2403.03490 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:44:27.534966Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T16:43:11.352389Z

Reference resolution

0 of 0 outbound references displayed

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  • unresolved0
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5d283391-7e59-4a1f-a294-0c79085d244c · inbound

Learning Optimal and Interpretable Summary Statistics of Galaxy Catalogs with SBI cites this paper.

Learning Optimal and Interpretable Summary Statistics of Galaxy Catalogs with SBI A comparative study of cosmological constraints from weak lensing using Convolutional Neural Networks

Reference 108

Resolution
unresolved
no resolver link, observed 2026-08-12T21:18:10.986697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:18:10.986697Z digest=sha256:59aaab9064b677ed263b9f3d8fb0246adf9431c42edb1f392b1ac85ad5425009

Observation f2629253-1bb3-4565-9052-542e3afc26cf · inbound

Cosmological Analysis with Calibrated Neural Quantile Estimation and Approximate Simulators cites this paper.

Cosmological Analysis with Calibrated Neural Quantile Estimation and Approximate Simulators A comparative study of cosmological constraints from weak lensing using Convolutional Neural Networks

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-23T16:43:11.355789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-23T16:42:50.485680Z digest=sha256:d6020ea94b750fe33bc0ca28fa7590a8ed1f498a81d19ee33eab5ecda79ad0bf

Observation 682bff4f-1f7c-4879-aed2-a1c15a5adc23 · inbound

Diffusion-based mass map reconstruction from weak lensing data cites this paper.

Diffusion-based mass map reconstruction from weak lensing data A comparative study of cosmological constraints from weak lensing using Convolutional Neural Networks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-08T23:21:44.995046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:21:44.995046Z digest=sha256:da28d4c3fc3b3c4d47d24a9efcb089311dda40a92845fb5eca9b993a5b298f56

Observation eeeb4faf-4230-4279-83f6-cfe2664b0e42 · inbound

Detecting Modeling Bias with Continuous Time Flow Models on Weak Lensing Maps cites this paper.

Detecting Modeling Bias with Continuous Time Flow Models on Weak Lensing Maps A comparative study of cosmological constraints from weak lensing using Convolutional Neural Networks

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-16T04:44:27.534966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:44:27.534966Z digest=sha256:d4d813d4d42a9f16232f8547da72f6d70549ba7a4f361389d69fc13a34c90d70

Observation 28b4c38a-c3cc-42f2-9b90-efb060c42a79 · inbound

Field-Level Comparison and Robustness Analysis of Cosmological N-body Simulations cites this paper.

Field-Level Comparison and Robustness Analysis of Cosmological N-body Simulations A comparative study of cosmological constraints from weak lensing using Convolutional Neural Networks

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T20:20:08.756954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:20:08.756954Z digest=sha256:c18a84a179bcc36651a6abfbec357a9c70e33a0a719bb4f5b02920ad7b8206c2