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Paper Citation Record · LEDGER

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators

As of 10 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2604.07438.

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

pith.paper-citation-record.v1
2604.07438 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:47:36.702238Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 6a7ecb6f-0654-4e7a-9ea3-616200660504 · outbound

This paper cites A., Marshall, P., & Oguri, M.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators A., Marshall, P., & Oguri, M

Reference 1

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Observation c01a8efa-664f-40ed-9c5c-5b6392111077 · outbound

This paper cites P., & Turok, N.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators P., & Turok, N

Reference 2

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Observation 1145235c-5fab-4f57-a223-73ba30e2de54 · outbound

This paper cites Constraining Effective Field Theories with Machine Learning.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Constraining Effective Field Theories with Machine Learning

Reference 3

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arxiv_id, observed 2026-05-11T06:31:01.866476Z

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Observation 2daf26ea-7c4a-403b-943c-514a18771c3f · outbound

This paper cites Mining gold from implicit models to improve likelihood-free inference.Proceedings of the National Academy of Sciences, 117(10):5242–5249.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Mining gold from implicit models to improve likelihood-free inference.Proceedings of the National Academy of Sciences, 117(10):5242–5249

Reference 4

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Observation 37ddfa1b-f320-4e85-94b8-ad099a377c03 · outbound

This paper cites 2019, ApJ, 886, 49, doi: 10.3847/1538-4357/ab4c41 Campeau-Poirier, `E., Perreault-Levasseur, L., Coogan, A., & Hezaveh, Y.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2019, ApJ, 886, 49, doi: 10.3847/1538-4357/ab4c41 Campeau-Poirier, `E., Perreault-Levasseur, L., Coogan, A., & Hezaveh, Y

Reference 5

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Observation e7bd6336-e18f-42a9-9012-9ceb62a3dbd4 · outbound

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LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Unresolved cited work

Reference 6

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Observation 1509782a-dda1-4a4a-91b5-dcd34a893292 · outbound

This paper cites One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses

Reference 7

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Observation f6fc0a4d-48f6-4154-bdea-ff41216581df · outbound

This paper cites Approximating Likelihood Ratios with Calibrated Discriminative Classifiers.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Approximating Likelihood Ratios with Calibrated Discriminative Classifiers

Reference 8

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Observation e5b9c0c7-1ab2-4295-8a60-d51a5206fa0c · outbound

This paper cites 2007, title Formation and Evolution of Galaxy Dark Matter Halos and Their Substructure , , 667, 859, 10.1086/520573.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2007, title Formation and Evolution of Galaxy Dark Matter Halos and Their Substructure , , 667, 859, 10.1086/520573

Reference 9

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Observation cf9c2bd2-2bb5-48eb-8cbf-66b071acf880 · outbound

This paper cites Investigating the Dark Energy Constraint from Strongly Lensed AGN at LSST-Scale.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Investigating the Dark Energy Constraint from Strongly Lensed AGN at LSST-Scale

Reference 10

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Observation 06151a8f-e9fd-4bc2-aab2-e8ff526466d7 · outbound

This paper cites 2025b, AJ, 170, 44, doi: 10.3847/1538-3881/add99f.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025b, AJ, 170, 44, doi: 10.3847/1538-3881/add99f

Reference 11

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Observation 0702fe5e-f139-4b55-b7dd-d9c3dcd3e01a · outbound

This paper cites Ferreira, Ultra-light dark matter, The Astronomy and Astrophysics Review29, 10.1007/s00159-021-00135-6 (2021).

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Ferreira, Ultra-light dark matter, The Astronomy and Astrophysics Review29, 10.1007/s00159-021-00135-6 (2021)

Reference 12

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Observation 6a4a757c-e8fe-4765-9808-fec1510b1089 · outbound

This paper cites 2025, ApJ, 989, 226, doi: 10.3847/1538-4357/adee20.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025, ApJ, 989, 226, doi: 10.3847/1538-4357/adee20

Reference 13

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Observation 010cc75a-d208-4cad-a507-2c55841069f5 · outbound

This paper cites keywords =.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators keywords =

Reference 14

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Observation 91f2261b-1add-46a8-a235-c2365e22da6f · outbound

This paper cites keywords =.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators keywords =

Reference 15

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Observation 4e3e4c58-6eef-44bc-9b0f-4068d95b94fb · outbound

This paper cites Deep residual learning for image recognition.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Deep residual learning for image recognition

Reference 16

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Observation 2629c668-f013-4162-a492-ab05b7e7b65a · outbound

This paper cites D., Dalal, N., Marrone, D.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators D., Dalal, N., Marrone, D

Reference 17

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Observation 0677d3c5-62ae-4627-bd36-b482473d5853 · outbound

This paper cites Nine-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Cosmological Parameter Results.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Nine-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Cosmological Parameter Results

Reference 18

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Observation a6c4cdf8-e296-49ab-ae6a-4efffa86e5a7 · outbound

This paper cites 2018, title Modeling evolution of dark matter substructure and annihilation boost , , 97, 123002, 10.1103/PhysRevD.97.123002.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2018, title Modeling evolution of dark matter substructure and annihilation boost , , 97, 123002, 10.1103/PhysRevD.97.123002

Reference 19

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Observation 9e207872-bbbb-4a98-8f68-1b99bedec5c0 · outbound

This paper cites B., Nightingale, J.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators B., Nightingale, J

Reference 20

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Observation e3ac5a60-5c43-4594-a708-a00902abc17e · outbound

This paper cites 85(6):1158--1161.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 85(6):1158--1161

Reference 21

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Observation bd6acea8-4895-425a-9f97-c1f04e56be1e · outbound

This paper cites Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

Reference 22

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Observation f532eecd-815d-49df-aaba-92102c4945d5 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Adam: A Method for Stochastic Optimization

Reference 23

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Observation 7884a8c8-3528-4ed0-8bd0-70bb01f84f3b · outbound

This paper cites 2007, ApJ, 671, 1135, doi: 10.1086/522878.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2007, ApJ, 671, 1135, doi: 10.1086/522878

Reference 24

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Observation a3a7a052-b529-4236-b147-bcbfce3a166d · outbound

This paper cites 2022, A&A, 668, A166, doi: 10.1051/0004-6361/202244978 LSST Science Collaboration, Abell, P.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2022, A&A, 668, A166, doi: 10.1051/0004-6361/202244978 LSST Science Collaboration, Abell, P

Reference 25

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Observation ccc7bf6f-a73c-4773-9b9d-d4e414266025 · outbound

This paper cites F., Frenk C.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators F., Frenk C

Reference 26

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Observation 8a135a7d-fc61-402e-9a50-6244f0d81095 · outbound

This paper cites 2025, JCAP, 2025, 053, doi: 10.1088/1475-7516/2025/05/053.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025, JCAP, 2025, 053, doi: 10.1088/1475-7516/2025/05/053

Reference 27

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Observation cb9ce653-909f-4ef6-bfc9-0406387bd1c0 · outbound

This paper cites K., & Poulin, V.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators K., & Poulin, V

Reference 28

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation dad5aff4-30ab-42d7-80ed-c49c243d323b · outbound

This paper cites 2014, ApJL, 793, L10, doi: 10.1088/2041-8205/793/1/L10 S´ ersic, J.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2014, ApJL, 793, L10, doi: 10.1088/2041-8205/793/1/L10 S´ ersic, J

Reference 29

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Observation 9e94068e-f0fe-4860-95e3-18104396f0cf · outbound

This paper cites I., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04416.x , http://adsabs.harvard.edu/abs/2001MNRAS.325..231O 325, 231.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators I., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04416.x , http://adsabs.harvard.edu/abs/2001MNRAS.325..231O 325, 231

Reference 30

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arxiv_id, observed 2026-05-10T17:40:40.679482Z

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Observation 3d82a834-9b26-4adb-8fe8-c1e04dd3944c · outbound

This paper cites T., Ogilvie G.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators T., Ogilvie G

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3068a543-c038-4cc6-be1e-9f1a981c938c · outbound

This paper cites Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c40033b9-2f51-42d1-be40-0d68d4695123 · outbound

This paper cites Likelihood-free inference with an improved cross-entropy estimator.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators Likelihood-free inference with an improved cross-entropy estimator

Reference 33

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verified exact
arxiv_id, observed 2026-05-10T17:40:40.693656Z

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Observation 493fc034-b6ab-4780-aaca-dd450bc904a1 · outbound

This paper cites B., 2015, @doi [ ] 10.1051/0004-6361/201526773 , http://adsabs.harvard.edu/abs/2015A.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators B., 2015, @doi [ ] 10.1051/0004-6361/201526773 , http://adsabs.harvard.edu/abs/2015A

Reference 34

Resolution
verified exact
doi, observed 2026-05-10T20:50:49.107384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 37e2f5f9-e3cf-4240-88e9-2c6ec5717709 · outbound

This paper cites W., Montefalcone , G., McDonough , E., & Freese , K.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators W., Montefalcone , G., McDonough , E., & Freese , K

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T17:40:40.691107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 611e7e46-69b6-4cd6-a14e-89cf2d54b8b8 · outbound

This paper cites J., Reeves J.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators J., Reeves J

Reference 36

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metadata mismatch
arxiv_id, observed 2026-05-10T20:50:49.111492Z

Source-reported events for the cited work

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source=pdf_text observed=2026-05-10T17:36:30.176638Z digest=sha256:f02f4bc9fc16f7fcfd8b4c19d05c4e14b683ebca69e796d3c7f26e7b7926268d

Observation 7c8ab618-b946-4a5e-9e35-92177bc8e658 · outbound

This paper cites 2025, arXiv e-prints, arXiv:2510.20778, doi: 10.48550/arXiv.2510.20778.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2025, arXiv e-prints, arXiv:2510.20778, doi: 10.48550/arXiv.2510.20778

Reference 37

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verified exact
arxiv_id, observed 2026-05-10T20:50:49.119024Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:36:30.176638Z digest=sha256:314b3c4f49bcd2dca346ec138aed5b29ba538d14398f5f32615cf1867ca49f48

Observation d41f4944-722f-46c5-afe1-3d0937a97694 · outbound

This paper cites D., Bolton, J.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators D., Bolton, J

Reference 38

Resolution
verified exact
doi, observed 2026-05-10T20:50:49.128270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:36:30.176638Z digest=sha256:434abb03fbf5f52aa1bbb19944230d0580e909a99bd8f9223f0f1d7611942fa3

Observation 606b7294-dade-4eae-8f82-9c421e5e8099 · outbound

This paper cites G., Matarrese, S., & Riotto, A.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators G., Matarrese, S., & Riotto, A

Reference 39

Resolution
verified exact
doi, observed 2026-05-10T17:40:40.686862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:36:30.176638Z digest=sha256:3794382f23493ed3a62bd2ec08ab3d4ff195f3271d36e84bc8b235f66ecc9bc6

Observation 633a83bf-5af7-4730-a19c-627baa45a5e5 · outbound

This paper cites 2023, PhRvD, 108, 023502, doi: 10.1103/PhysRevD.108.023502.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators 2023, PhRvD, 108, 023502, doi: 10.1103/PhysRevD.108.023502

Reference 40

Resolution
verified exact
doi, observed 2026-05-10T17:40:40.688629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:36:30.176638Z digest=sha256:b9e444349f09a3f3191545a473db8633591da30d89c32a3113ce888b38fa0738

Observation 3c6822f4-19b3-4c55-b301-d94e7eb8ca6f · outbound

This paper cites keywords =.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators keywords =

Reference 41

Resolution
metadata mismatch
doi, observed 2026-05-10T20:50:49.093169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:36:30.176638Z digest=sha256:916f0a8e9e3ee3105a8932bceb8b1aa13139926728154a6d34dcb4784420c7b9

Observation 5923ad35-a751-40d0-bce9-fe73777a1b4b · outbound

This paper cites A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-Scale Structure Using Sequential Methods.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-Scale Structure Using Sequential Methods

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-10T17:40:40.677063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:36:30.176638Z digest=sha256:3f2e9a6e0cb4fe46b75787b006e96234b57d8e00498fbd92ccc07bfda090a01e

Observation e915fef1-3de6-4eb5-bcbd-011042d9901d · outbound

This paper cites C ¸ ., & Dvorkin, C.

LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators C ¸ ., & Dvorkin, C

Reference 43

Resolution
verified exact
doi, observed 2026-05-10T20:50:49.080627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:36:30.176638Z digest=sha256:a45e16050b0bbbbccb428f8265e4fd1986263ccdbda4593b6d940aa2010bcfcf

Pith citing papers

Observation bb22a1f7-ac16-449e-bf96-e7c61c6753b7 · inbound

Strong Gravitational Lensing Posterior Sampling in Pixel-Space Using Diffusion Models and Recurrent Inference Machines cites this paper.

Strong Gravitational Lensing Posterior Sampling in Pixel-Space Using Diffusion Models and Recurrent Inference Machines LSST Strong Lensing Systems Dark Matter Sensitivity Analysis with Neural Ratio Estimators

Reference 82

Resolution
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local_arxiv, observed 2026-08-01T12:49:38.774781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-01T12:47:36.702238Z digest=sha256:2ff63bb531e95a2cdf016c47bb7d037452c4ecab55a0bd605b26ff17f402badd