Paper Citation Record · LEDGER

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction

As of 19 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2507.21516.

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

pith.paper-citation-record.v1
2507.21516 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:45:22.488186Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T18:28:42.373841Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T23:07:26.876301Z

Reference resolution

43 of 43 outbound references displayed

verified exact2
verified fuzzy30
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc3f5e53-b0c3-4118-84ba-242fd05e7aef · outbound

This paper cites Nature methods 18(1), 9–14 (2021).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature methods 18(1), 9–14 (2021)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.813107Z

Source-reported events for the cited work

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Observation 34aeb6f1-9b28-4629-bb53-ab373e9b90b2 · outbound

This paper cites Science 353(6294), 78–82 (2016).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Science 353(6294), 78–82 (2016)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.806100Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9c305f38-2574-4a36-9251-061f840755aa · outbound

This paper cites Science 363(6434), 1463–1467 (2019).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Science 363(6434), 1463–1467 (2019)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.798081Z

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Observation b4e4453c-be25-4041-b7b4-f47783b866e0 · outbound

This paper cites Science 361(6400), 5691 (2018).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Science 361(6400), 5691 (2018)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.791697Z

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Observation ddbd3151-0ded-4f5b-854a-ef722f9fcaa9 · outbound

This paper cites Nature communications 11(1), 3877 (2020).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature communications 11(1), 3877 (2020)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.785205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 00d1e950-19ed-4343-838f-4d2103fd3f7e · outbound

This paper cites Advances in Neural Information Processing Systems 36, 70626–70637 (2023).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Advances in Neural Information Processing Systems 36, 70626–70637 (2023)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.779179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2861809e-6568-4487-8a89-6e3c259da347 · outbound

This paper cites Nature medicine 24(10), 1559–1567 (2018).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature medicine 24(10), 1559–1567 (2018)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.770674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9edbc683-fc42-48fc-865f-c43eb132ee42 · outbound

This paper cites Nature medicine 25(8), 1301–1309 (2019).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature medicine 25(8), 1301–1309 (2019)

Reference 8

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Source-reported events for the cited work

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Observation 59291a2d-c0a5-4383-8a57-bb3f55c11c2f · outbound

This paper cites ASIGN: An Anatomy-aware Spatial Imputation Graphic Network for 3D Spatial Transcriptomics.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction ASIGN: An Anatomy-aware Spatial Imputation Graphic Network for 3D Spatial Transcriptomics

Reference 9

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff70218c-ae7b-4233-9114-185daf47bd4a · outbound

This paper cites In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.760241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32265d6e-3daf-4bc7-b4c0-355c21c9cdf2 · outbound

This paper cites Science Advances 6(26), 3446 (2020) https://doi.org/10.1126/sciadv.abb3446.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Science Advances 6(26), 3446 (2020) https://doi.org/10.1126/sciadv.abb3446

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 82e01212-dc69-4476-9550-da7585b4e222 · outbound

This paper cites Nature Communications 12(1), 6012 (2021) https://doi.org/10.1038/ s41467-021-26271-2.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature Communications 12(1), 6012 (2021) https://doi.org/10.1038/ s41467-021-26271-2

Reference 12

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T12:45:22.753198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e5c63258-5298-4fbc-87c8-ae3c0d81589f · outbound

This paper cites Nature Genetics 53(9), 1334–1347 (2021) https://doi.org/10.1038/s41588-021-00904-2.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature Genetics 53(9), 1334–1347 (2021) https://doi.org/10.1038/s41588-021-00904-2

Reference 13

Resolution: verified exact; doi, observed 2026-08-06T12:45:22.509942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ab97ba28-13ac-4546-ac7f-7a73bb7e365f · outbound

This paper cites Medical image analysis 58, 101544 (2019).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Medical image analysis 58, 101544 (2019)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.747275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 831dc42a-6e8d-428d-a09c-2f0308791c5d · outbound

This paper cites Nature communications 14(1), 3459 18 (2023).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature communications 14(1), 3459 18 (2023)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.741418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 33b82899-cefa-4b49-96df-676cf1039cdc · outbound

This paper cites IEEE journal of biomedical and health informatics 25(2), 325–336 (2020).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction IEEE journal of biomedical and health informatics 25(2), 325–336 (2020)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.733163Z

Source-reported events for the cited work

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Observation 20dfbb68-3a7b-48ed-8694-4b5e0852b7a9 · outbound

This paper cites Interna- tional journal of computer vision 60, 91–110 (2004).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Interna- tional journal of computer vision 60, 91–110 (2004)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.726019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8c2f9a8f-f821-4f23-9256-f3daec8400a6 · outbound

This paper cites an unresolved cited work.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-06T12:45:22.719621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 785cb420-b4c2-4423-a7fc-5b933e5c42a4 · outbound

This paper cites In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.712522Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 90db01b0-049c-41e1-8c14-c7ec22f51db6 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Denoising Diffusion Probabilistic Models

Reference 20

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Observation 8ed09e15-8262-460b-a80a-b5c8c3fa1e5a · outbound

This paper cites Nature Medicine 30(3), 863–874 (2024).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature Medicine 30(3), 863–874 (2024)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.707182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7ae16983-c4e7-4d31-a565-48bd6a390cbe · outbound

This paper cites Available at: https://www.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Available at: https://www

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.700619Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7a74766b-5122-468e-b66c-c9abab3b75f8 · outbound

This paper cites Cell systems 14(5), 404–417 (2023).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Cell systems 14(5), 404–417 (2023)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.694898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7ab7a56e-5bc6-4ab0-8b15-2fb2851cdca1 · outbound

This paper cites Briefings in Bioinformatics 24(2), 013 (2023).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Briefings in Bioinformatics 24(2), 013 (2023)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.688717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f09bba74-f2d8-49b9-bdb7-ce3ae7fb6245 · outbound

This paper cites Adversarial Feature Alignment: Balancing Robustness and Accuracy in Deep Learning via Adversarial Training.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Adversarial Feature Alignment: Balancing Robustness and Accuracy in Deep Learning via Adversarial Training

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 105149d1-1219-4ade-ad08-142729d9358e · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.683037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 368726c2-2858-48b1-9519-787554b8c77b · outbound

This paper cites Joint Distribution Alignment via Adversarial Learning for Domain Adaptive Object Detection.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Joint Distribution Alignment via Adversarial Learning for Domain Adaptive Object Detection

Reference 27

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T12:45:22.570375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1ee82cc3-7684-4162-b0aa-b4ec36023989 · outbound

This paper cites Pattern Recognition 108, 107539 (2020) 19.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Pattern Recognition 108, 107539 (2020) 19

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.676108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5fa5a15b-38f6-4799-bc28-9a2c8e78b570 · outbound

This paper cites In: Proceedings of the IEEE Winter Conference on Applications of Computer Vision, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the IEEE Winter Conference on Applications of Computer Vision, pp

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.670595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d008c95e-b803-4103-9603-18461393ad31 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence 39(8), 1634–1640 (2017).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction IEEE Transactions on Pattern Analysis and Machine Intelligence 39(8), 1634–1640 (2017)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.661576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ab3b25e1-d921-4414-b6e7-8f14d02d4d40 · outbound

This paper cites In: Proceedings of the 36th Conference on Neural Information Processing Systems, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the 36th Conference on Neural Information Processing Systems, pp

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.655716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e65c1b71-434a-42fc-9367-93d7d05c397c · outbound

This paper cites AMA-SAM: Adversarial Multi-Domain Alignment of Segment Anything Model for High-Fidelity Histology Nuclei Segmentation.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction AMA-SAM: Adversarial Multi-Domain Alignment of Segment Anything Model for High-Fidelity Histology Nuclei Segmentation

Reference 32

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T12:45:22.560080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 21e5f865-737d-4638-af61-a145344c8212 · outbound

This paper cites Bridging Contrastive Learning and Domain Adaptation: Theoretical Perspective and Practical Application.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Bridging Contrastive Learning and Domain Adaptation: Theoretical Perspective and Practical Application

Reference 33

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T12:45:22.550411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2d22a2c8-0ccd-497c-9179-306891bbe6f0 · outbound

This paper cites Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation

Reference 34

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T12:45:22.538181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 642359bc-79cb-465c-8d3b-6ba855ae1ed9 · outbound

This paper cites In: Proceedings of the Fifth Conference on Health, Inference, and Learning, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the Fifth Conference on Health, Inference, and Learning, pp

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.649320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3ed24cef-f184-450d-8a30-9b967e226b32 · outbound

This paper cites Contrastive Semi-supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Contrastive Semi-supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures

Reference 36

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T12:45:22.528320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 48e5d309-8cc9-4dd3-8487-8b1c41bfc6c2 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.641204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 975fa4ca-dc0e-4620-ab6a-1e92d06c12d1 · outbound

This paper cites Nature Machine Intelligence 5(8), 487–499 (2023).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Nature Machine Intelligence 5(8), 487–499 (2023)

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.633806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 63df377f-627c-4394-8c7e-d710f9642e14 · outbound

This paper cites In: Proceedings of the 39th International Conference on Machine Learning, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the 39th International Conference on Machine Learning, pp

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.626121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e30c011b-fc0c-4fe6-8bbf-4c6b5ffd1556 · outbound

This paper cites In: Proceedings of the 20 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the 20 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.619350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 00139ba4-9afd-4752-961c-775a8267dd7d · outbound

This paper cites Journal of Medical Imaging 8(4), 1–12 (2021).

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction Journal of Medical Imaging 8(4), 1–12 (2021)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.612923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eeacf2c3-5985-495b-9443-c11a2ed93648 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp.

ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.605417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 111dd245-d943-4b96-9991-d4630bd5ffe8 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp.

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:45:22.598524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 29c191a7-ea9e-43b0-ad05-da03364a8b39 · inbound

SNR-ST-Mix: Sample-specific Neighborhood Regression Mixup for Augmented Spatial Transcriptomics Imputation with Deep Neural Network cites this paper.

SNR-ST-Mix: Sample-specific Neighborhood Regression Mixup for Augmented Spatial Transcriptomics Imputation with Deep Neural Network ST-DAI: Single-shot 2.5D Spatial Transcriptomics with Intra-Sample Domain Adaptive Imputation for Cost-efficient 3D Reconstruction

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:07:26.878123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.