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Paper Citation Record · LEDGER

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade

As of 14 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2512.01572.

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pith.paper-citation-record.v1
2512.01572 v3

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Outbound references

Observation d3534375-2c84-4bc3-a473-765f6eba9668 · outbound

This paper cites an unresolved cited work.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Unresolved cited work

Reference 1

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Observation 9a0c8d1a-9157-49aa-84f2-e728905f2c34 · outbound

This paper cites Nonlinear Processes in Geophysics13(2), 151–159 (2006).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Nonlinear Processes in Geophysics13(2), 151–159 (2006)

Reference 2

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Observation 74b3cf0e-7040-4dff-a4c0-4e4050092afa · outbound

This paper cites Wiley Interdisciplinary Reviews: Climate Change9(5), 535 (2018).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Wiley Interdisciplinary Reviews: Climate Change9(5), 535 (2018)

Reference 3

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This paper cites IEEE Control Systems Magazine38(3), 63–86 (2018).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade IEEE Control Systems Magazine38(3), 63–86 (2018)

Reference 4

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This paper cites IEEE Transactions on Geoscience and Remote Sensing48(12), 4285–4295 (2010).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade IEEE Transactions on Geoscience and Remote Sensing48(12), 4285–4295 (2010)

Reference 5

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Observation 73f88532-d2e7-4280-91cb-301ed8ad94fa · outbound

This paper cites In: 2014 IEEE Geoscience and Remote Sensing Symposium, pp.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: 2014 IEEE Geoscience and Remote Sensing Symposium, pp

Reference 6

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Observation b6a941ba-6d8e-44d4-aeac-333df5334b3c · outbound

This paper cites Nature Reviews Physics5(9), 536–545 (2023).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Nature Reviews Physics5(9), 536–545 (2023)

Reference 7

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Observation 698e85c9-2047-4c61-9169-dacb625e4292 · outbound

This paper cites Europhysics Letters142(2), 23001 (2023).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Europhysics Letters142(2), 23001 (2023)

Reference 8

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This paper cites Courier Corporation, San Francisco (2014).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Courier Corporation, San Francisco (2014)

Reference 9

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This paper cites Applied and Computational Harmonic Analysis65, 374–406 (2023).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Applied and Computational Harmonic Analysis65, 374–406 (2023)

Reference 10

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This paper cites IEEE Transactions on information theory52(2), 489–509 (2006).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade IEEE Transactions on information theory52(2), 489–509 (2006)

Reference 11

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Observation 818d9a9a-ce49-44db-a9b4-6e2fbc764b99 · outbound

This paper cites IEEE Transactions on Instrumentation and Measurement67(1), 185–195 (2017).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade IEEE Transactions on Instrumentation and Measurement67(1), 185–195 (2017)

Reference 12

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This paper cites IEEE Transactions on Image Processing29, 375–388 (2019).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade IEEE Transactions on Image Processing29, 375–388 (2019)

Reference 13

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This paper cites Computer-Aided Civil and Infrastructure Engineering35(7), 685–700 (2020).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Computer-Aided Civil and Infrastructure Engineering35(7), 685–700 (2020)

Reference 14

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This paper cites IEEE Geoscience and Remote Sensing Magazine10(4), 32–69 (2022).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade IEEE Geoscience and Remote Sensing Magazine10(4), 32–69 (2022)

Reference 15

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This paper cites Nature Machine Intelligence3(11), 945–951 (2021).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Nature Machine Intelligence3(11), 945–951 (2021)

Reference 16

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Observation ece2ec67-4b56-44d1-af6f-38b5524f6c69 · outbound

This paper cites Computer Physics Communications308, 109464 (2025).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Computer Physics Communications308, 109464 (2025)

Reference 17

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This paper cites Energy, 134644 (2025).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Energy, 134644 (2025)

Reference 18

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This paper cites Engineering Applications of Artificial Intelligence144, 110079 (2025).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Engineering Applications of Artificial Intelligence144, 110079 (2025)

Reference 19

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This paper cites JSTOR (1978).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade JSTOR (1978)

Reference 20

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This paper cites Acta Numerica28, 1–174 (2019).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Acta Numerica28, 1–174 (2019)

Reference 21

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This paper cites Communications of the ACM63(11), 139–144 (2020).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Communications of the ACM63(11), 139–144 (2020)

Reference 22

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This paper cites Advances in neural information processing systems33, 6840–6851 (2020).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Advances in neural information processing systems33, 6840–6851 (2020)

Reference 23

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This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Score-Based Generative Modeling through Stochastic Differential Equations

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

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 25

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

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 26

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

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp

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Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade IEEE Transactions on Medical Imaging43(5), 1853–1865 (2024)

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Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Deep Learning in Medical Image Analysis: Challenges and Applications, 23–44 (2020)

Reference 29

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Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Science 386(6723), 9336 (2024)

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Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade From Zero to Turbulence: Generative Modeling for 3D Flow Simulation

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This paper cites Advances in neural information processing systems36, 45259–45287 (2023).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Advances in neural information processing systems36, 45259–45287 (2023)

Reference 32

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This paper cites Nature Machine Intelligence6(4), 393–403 (2024).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Nature Machine Intelligence6(4), 393–403 (2024)

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Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Physics of Fluids31(12) (2019)

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Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Journal of Computational Physics478, 111972 (2023)

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Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models

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Observation 11a06d16-07d9-4ef8-894e-ef0d032454ce · outbound

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

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

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Observation 38d86ec8-0ac0-45f6-855d-77321e4d4a98 · outbound

This paper cites Advances in Neural Information Processing Systems34, 13242–13254 (2021).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Advances in Neural Information Processing Systems34, 13242–13254 (2021)

Reference 38

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Observation 97577227-5013-4a75-a26a-42dc8e009a9e · outbound

This paper cites Nature Communications15(1), 10416 (2024).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Nature Communications15(1), 10416 (2024)

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Observation 35669add-7628-4737-a656-a0fdd85acea3 · outbound

This paper cites Nature Machine Intelligence6(12), 1566–1579 (2024).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Nature Machine Intelligence6(12), 1566–1579 (2024)

Reference 40

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Observation 9d855791-c55a-4f8d-be6d-29d317b08fc8 · outbound

This paper cites Advances in Neural Information Processing Systems35, 25683–25696 (2022).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Advances in Neural Information Processing Systems35, 25683–25696 (2022)

Reference 41

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Observation f597c5a8-0f71-4672-ad80-997c09d667ef · outbound

This paper cites arXiv preprint arXiv:2506.07902 (2025).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade arXiv preprint arXiv:2506.07902 (2025)

Reference 42

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Observation 2b53f808-f1dd-447c-9810-7d2fb5a48fb5 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: International Conference on Machine Learning, pp

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Observation dda555fb-1b3d-499e-9c6d-2520a14857fe · outbound

This paper cites IEEE transactions on pattern analysis and machine intelligence45(4), 4713–4726 (2022).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade IEEE transactions on pattern analysis and machine intelligence45(4), 4713–4726 (2022)

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Observation 3d8100b7-25a8-4d51-ae83-4855a760a4fa · outbound

This paper cites Journal of Machine Learning Research23(47), 1–33 (2022).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Journal of Machine Learning Research23(47), 1–33 (2022)

Reference 45

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Observation 345675c6-028d-4464-8b15-8be9e86b6b12 · outbound

This paper cites Autoencoders in Function Space.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Autoencoders in Function Space

Reference 46

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Observation b243dda5-970b-4d10-a1a6-e1c04b211b24 · outbound

This paper cites Scientific reports10(1), 3302 (2020).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Scientific reports10(1), 3302 (2020)

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Observation ca553c51-0ce5-42d3-8499-098c81f6febc · outbound

This paper cites Nature Communications15(1), 1834 (2024) 19.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Nature Communications15(1), 1834 (2024) 19

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Observation 5be282f3-37df-42f0-9be4-7148086efce8 · outbound

This paper cites Communications Physics6(1), 319 (2023).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Communications Physics6(1), 319 (2023)

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Observation 860b98a4-5eb7-4aba-9e7e-fc3168f8849b · outbound

This paper cites Neural Operator: Graph Kernel Network for Partial Differential Equations.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Neural Operator: Graph Kernel Network for Partial Differential Equations

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Observation 887153f5-0f36-4798-8bd2-150ffc365fc3 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Fourier Neural Operator for Parametric Partial Differential Equations

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Observation 396545b5-6a4b-4764-b664-11a8d2d21c70 · outbound

This paper cites Advances in neural information processing systems33, 7537–7547 (2020).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Advances in neural information processing systems33, 7537–7547 (2020)

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Observation 61728715-8f9f-4bcf-9d6b-3e83f5e6c51b · outbound

This paper cites Nature machine intelligence3(3), 218–229 (2021).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Nature machine intelligence3(3), 218–229 (2021)

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Observation f97c08c7-d005-4ad0-aebe-978f2e43cc2d · outbound

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

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 54

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Observation e6339f39-3870-4597-8237-c89ce73eb649 · outbound

This paper cites an unresolved cited work.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Unresolved cited work

Reference 55

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Observation 0bfb4dfa-2546-461f-9afd-2b20d209beff · outbound

This paper cites In: China National Conference on Chinese Computational Linguistics, pp.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: China National Conference on Chinese Computational Linguistics, pp

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Observation c12a5bcf-b5a5-4ae4-9934-93d85dfaadff · outbound

This paper cites Journal of machine learning research 21(140), 1–67 (2020).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Journal of machine learning research 21(140), 1–67 (2020)

Reference 57

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Observation 26395ee2-201d-4340-979b-9e74430ff675 · outbound

This paper cites In: Breakthroughs in Statistics: Foundations and Basic Theory, pp.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade In: Breakthroughs in Statistics: Foundations and Basic Theory, pp

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Observation 1498870f-03b3-4304-8550-088306112dcf · outbound

This paper cites Journal of machine learning research9(Nov), 2579–2605 (2008).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Journal of machine learning research9(Nov), 2579–2605 (2008)

Reference 59

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Observation 54fcef1b-8933-4122-822c-4dea818cd50d · outbound

This paper cites Scientific data7(1), 145 (2020).

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade Scientific data7(1), 145 (2020)

Reference 60

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Observation 906e770d-c821-40be-a918-b1cbb3e85f55 · outbound

This paper cites https://doi.org/10.48670/ moi-00016 20.

Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade https://doi.org/10.48670/ moi-00016 20

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