Fusion of multi-source precipitation records via coordinate-based generative model | Paper Citation Record

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This paper cites & Wenz, L.

Fusion of multi-source precipitation records via coordinate-based generative model & Wenz, L

Reference 1

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This paper cites & Portmann, R.

Fusion of multi-source precipitation records via coordinate-based generative model & Portmann, R

Reference 2

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

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This paper cites & Feingold, G.

Fusion of multi-source precipitation records via coordinate-based generative model & Feingold, G

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

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This paper cites F., Mooney, P.

Fusion of multi-source precipitation records via coordinate-based generative model F., Mooney, P

Reference 6

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 7

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This paper cites & Molini, A.

Fusion of multi-source precipitation records via coordinate-based generative model & Molini, A

Reference 8

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This paper cites The cumulus parameterization problem: Past, present, and future.

Fusion of multi-source precipitation records via coordinate-based generative model The cumulus parameterization problem: Past, present, and future

Reference 9

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 10

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This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 11

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This paper cites & Huffman, G.

Fusion of multi-source precipitation records via coordinate-based generative model & Huffman, G

Reference 12

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Observation f7b11bba-0971-4913-bcab-2b78e9a7cc02 · outbound

This paper cites Y.et al.The global precipitation measurement mission.Bulletin of the American meteorological Society95, 701–722 (2014).

Fusion of multi-source precipitation records via coordinate-based generative model Y.et al.The global precipitation measurement mission.Bulletin of the American meteorological Society95, 701–722 (2014)

Reference 13

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Observation 659dddae-0fd3-44fa-aa9b-a3153b7798a0 · outbound

This paper cites & Meneguzzo, F.

Fusion of multi-source precipitation records via coordinate-based generative model & Meneguzzo, F

Reference 14

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This paper cites & Brunet, G.

Fusion of multi-source precipitation records via coordinate-based generative model & Brunet, G

Reference 15

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This paper cites J.et al.Is precipitation a good metric for model performance?Bulletin of the American Meteorological Society100, 223–233 (2019).

Fusion of multi-source precipitation records via coordinate-based generative model J.et al.Is precipitation a good metric for model performance?Bulletin of the American Meteorological Society100, 223–233 (2019)

Reference 16

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This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 17

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Observation f30a84da-45c0-45b2-b1eb-f2d59a73136c · outbound

This paper cites Journal of Geophysical Research: Atmospheres123, 814–834 (2018).

Fusion of multi-source precipitation records via coordinate-based generative model Journal of Geophysical Research: Atmospheres123, 814–834 (2018)

Reference 18

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This paper cites M.et al.Rf-mep: A novel random forest method for merging gridded precipitation products and ground-based measurements.Remote Sensing of Environment239, 111606 (2020).

Fusion of multi-source precipitation records via coordinate-based generative model M.et al.Rf-mep: A novel random forest method for merging gridded precipitation products and ground-based measurements.Remote Sensing of Environment239, 111606 (2020)

Reference 19

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This paper cites & Wen, Y.

Fusion of multi-source precipitation records via coordinate-based generative model & Wen, Y

Reference 20

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This paper cites K., Rathinasamy, M.

Fusion of multi-source precipitation records via coordinate-based generative model K., Rathinasamy, M

Reference 21

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This paper cites & Xiong, A.-Y.

Fusion of multi-source precipitation records via coordinate-based generative model & Xiong, A.-Y

Reference 22

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This paper cites M., Sivakumar, B.

Fusion of multi-source precipitation records via coordinate-based generative model M., Sivakumar, B

Reference 23

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 24

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 25

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 26

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This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

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This paper cites & Wang, G.

Fusion of multi-source precipitation records via coordinate-based generative model & Wang, G

Reference 28

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 29

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 30

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This paper cites & Closas, P.

Fusion of multi-source precipitation records via coordinate-based generative model & Closas, P

Reference 31

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This paper cites GenCast: Diffusion-based ensemble forecasting for medium-range weather.

Fusion of multi-source precipitation records via coordinate-based generative model GenCast: Diffusion-based ensemble forecasting for medium-range weather

Reference 32

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Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 33

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This paper cites Auto-Encoding Variational Bayes.

Fusion of multi-source precipitation records via coordinate-based generative model Auto-Encoding Variational Bayes

Reference 34

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This paper cites J., Mohamed, S.

Fusion of multi-source precipitation records via coordinate-based generative model J., Mohamed, S

Reference 35

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This paper cites & Abbeel, P.

Fusion of multi-source precipitation records via coordinate-based generative model & Abbeel, P

Reference 36

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This paper cites Denoising Diffusion Implicit Models.

Fusion of multi-source precipitation records via coordinate-based generative model Denoising Diffusion Implicit Models

Reference 37

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Observation f2789328-ef39-44ea-898e-3621f04a3ef4 · outbound

This paper cites Diffusion Models Beat GANs on Image Synthesis.

Fusion of multi-source precipitation records via coordinate-based generative model Diffusion Models Beat GANs on Image Synthesis

Reference 38

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This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 39

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This paper cites A Survey on Diffusion Models for Inverse Problems.

Fusion of multi-source precipitation records via coordinate-based generative model A Survey on Diffusion Models for Inverse Problems

Reference 40

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This paper cites URL https://arxiv.org/abs/2503.11043.

Fusion of multi-source precipitation records via coordinate-based generative model URL https://arxiv.org/abs/2503.11043

Reference 41

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Observation 50a73406-6d88-4fda-acc8-b31df082da3b · outbound

This paper cites & Boers, N.

Fusion of multi-source precipitation records via coordinate-based generative model & Boers, N

Reference 42

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Observation 8b915727-49b8-407b-9e2e-b78ddb1973bc · outbound

This paper cites Diffusion is spectral autoregression (2024).

Fusion of multi-source precipitation records via coordinate-based generative model Diffusion is spectral autoregression (2024)

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.460809Z

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Observation db4ec7f3-25aa-4fc5-8c80-f7c07ed16c4b · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Fusion of multi-source precipitation records via coordinate-based generative model U-Net: Convolutional Networks for Biomedical Image Segmentation

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This paper cites A.et al.Are climate model simulations of clouds improving? an evaluation using the ISCCP simulator.Journal of Geophysical Research: Atmospheres118, 1329–1342 (2013).

Fusion of multi-source precipitation records via coordinate-based generative model A.et al.Are climate model simulations of clouds improving? an evaluation using the ISCCP simulator.Journal of Geophysical Research: Atmospheres118, 1329–1342 (2013)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.450722Z

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Observation c93d2232-573d-4734-ba0d-0569479773c0 · outbound

This paper cites 6): A Python- based diagnostics package for Earth system models evaluation.Geoscientific model development discussions2022, 1–35 (2022).

Fusion of multi-source precipitation records via coordinate-based generative model 6): A Python- based diagnostics package for Earth system models evaluation.Geoscientific model development discussions2022, 1–35 (2022)

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.437939Z

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This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 47

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This paper cites & Huffman, G.

Fusion of multi-source precipitation records via coordinate-based generative model & Huffman, G

Reference 48

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This paper cites & Huffman, G.

Fusion of multi-source precipitation records via coordinate-based generative model & Huffman, G

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.408019Z

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This paper cites URL https://www.ecmwf.

Fusion of multi-source precipitation records via coordinate-based generative model URL https://www.ecmwf

Reference 50

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Observation c9cbc082-1ea2-479b-b7c5-677fb278efda · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.384417Z

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Observation 13202e30-31f9-4e23-80ef-73e53cd3782d · outbound

This paper cites E.et al.Mswep: 3-hourly 0.25 global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data.Hydrology and Earth System Sciences 21, 589–615 (2017).

Fusion of multi-source precipitation records via coordinate-based generative model E.et al.Mswep: 3-hourly 0.25 global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data.Hydrology and Earth System Sciences 21, 589–615 (2017)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.374080Z

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This paper cites A perspective on the future of CMIP.AGU Advances5, e2023A V001086 (2024).

Fusion of multi-source precipitation records via coordinate-based generative model A perspective on the future of CMIP.AGU Advances5, e2023A V001086 (2024)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.361433Z

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Observation ab161c9c-5d9d-40e2-8e22-44a6ac9f0110 · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 54

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Observation 0a5c0506-17fd-4896-8eec-7eee50863db7 · outbound

This paper cites Entity Embeddings of Categorical Variables.

Fusion of multi-source precipitation records via coordinate-based generative model Entity Embeddings of Categorical Variables

Reference 55

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Observation aadc58f2-446e-4d5f-8c0f-b09fc68be0d1 · outbound

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

Fusion of multi-source precipitation records via coordinate-based generative model Score-Based Generative Modeling through Stochastic Differential Equations

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Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.753546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af2eab4d-2610-413d-9b95-875110f63cc0 · outbound

This paper cites & Ermon, S.

Fusion of multi-source precipitation records via coordinate-based generative model & Ermon, S

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.341007Z

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.

Observation 1f180354-5338-4abf-9c17-8fec6bfd50aa · outbound

This paper cites Understanding Diffusion Models: A Unified Perspective.

Fusion of multi-source precipitation records via coordinate-based generative model Understanding Diffusion Models: A Unified Perspective

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.761340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0714ce3b-89c0-4ec7-9b32-4dc3645b90e3 · outbound

This paper cites $\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States.

Fusion of multi-source precipitation records via coordinate-based generative model $\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.765702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d10b1135-9818-4294-babc-232ccd5541d2 · outbound

This paper cites Infinite-Dimensional Diffusion Models.

Fusion of multi-source precipitation records via coordinate-based generative model Infinite-Dimensional Diffusion Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.769344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbf2c944-5b39-4562-be1c-e94c7897f149 · outbound

This paper cites Functional Diffusion.

Fusion of multi-source precipitation records via coordinate-based generative model Functional Diffusion

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:07:50.991696Z

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.

Observation f35e8346-6e54-4c53-898c-ceac62a2949c · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.331674Z

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.

Observation 4e5c32f8-5e45-40d4-87f5-2e2dcb7bbf13 · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.321174Z

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.

Observation 18efbb18-e0e8-4d53-8298-d3c66279c188 · outbound

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

Fusion of multi-source precipitation records via coordinate-based generative model Neural Operator: Graph Kernel Network for Partial Differential Equations

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.783412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80e6f521-2c56-4c5d-bc09-e63b06e15b5d · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.311770Z

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.

Observation 84ed9891-f995-423a-8911-6a20a4275770 · outbound

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

Fusion of multi-source precipitation records via coordinate-based generative model Fourier Neural Operator for Parametric Partial Differential Equations

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.790186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f20dafca-0ebc-45d3-8534-5ccf909bbd81 · outbound

This paper cites TorchSparse: Efficient Point Cloud Inference Engine.

Fusion of multi-source precipitation records via coordinate-based generative model TorchSparse: Efficient Point Cloud Inference Engine

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:07:50.954512Z

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.

Observation ed19b5ab-015b-4c17-a28e-a7ce8e4606ea · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.301795Z

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.

Observation 9245da8b-b1d1-4e91-9fda-59407c2aadd9 · outbound

This paper cites Diffusion Posterior Sampling for General Noisy Inverse Problems.

Fusion of multi-source precipitation records via coordinate-based generative model Diffusion Posterior Sampling for General Noisy Inverse Problems

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.801007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0510c5a9-8a4a-4be8-a783-abc6a306115f · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.292041Z

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.

Observation 74a9080a-25d8-478b-87c3-5896a4934560 · outbound

This paper cites RePaint: Inpainting using Denoising Diffusion Probabilistic Models.

Fusion of multi-source precipitation records via coordinate-based generative model RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.808163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc5ae914-8e1d-4447-b738-9cb0dfeca96f · outbound

This paper cites Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models.

Fusion of multi-source precipitation records via coordinate-based generative model Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.811621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09837287-9b41-4cf6-834e-a3ac81d5a9ac · outbound

This paper cites SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.

Fusion of multi-source precipitation records via coordinate-based generative model SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.815072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b546795-f28e-4a1e-a687-1ca80a296048 · outbound

This paper cites & Raftery, A.

Fusion of multi-source precipitation records via coordinate-based generative model & Raftery, A

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.282004Z

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.

Observation e55565b2-d217-42e6-98be-96771e2662fc · outbound

This paper cites A primer for eof analysis of climate data.Department of Meteorology, University of Reading1, 3 (2004).

Fusion of multi-source precipitation records via coordinate-based generative model A primer for eof analysis of climate data.Department of Meteorology, University of Reading1, 3 (2004)

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.271374Z

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.

Observation a524d7c5-8885-492e-a2da-7a687da51948 · outbound

This paper cites 0).Geoscientific Model Development12, 4185–4219 (2019).

Fusion of multi-source precipitation records via coordinate-based generative model 0).Geoscientific Model Development12, 4185–4219 (2019)

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.260475Z

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.

Observation 5f53e6e9-8cb5-4ddb-b3f1-e965f7950074 · outbound

This paper cites J.et al.Nasa global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG).Algorithm theoretical basis document (ATBD) version4, 30 (2015).

Fusion of multi-source precipitation records via coordinate-based generative model J.et al.Nasa global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG).Algorithm theoretical basis document (ATBD) version4, 30 (2015)

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.250318Z

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.

Observation baba2142-ff04-4ba6-89b2-04245dbbf90b · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.239020Z

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.

Observation 618405dd-bfd8-4a6f-8b3c-a0fde5c74790 · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.228914Z

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.

Observation 0c4d8313-c8f3-47ea-b460-b8fb5c9b6233 · outbound

This paper cites & Messori, G.

Fusion of multi-source precipitation records via coordinate-based generative model & Messori, G

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.218384Z

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.

Observation eb6bb813-33c8-4013-b5b6-d0bd664571f2 · outbound

This paper cites How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion.

Fusion of multi-source precipitation records via coordinate-based generative model How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.842560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb8a22ae-9b4f-476e-9e63-ea9266b759ec · outbound

This paper cites Advances in Neural Information Processing Systems36, 288–313 (2023).

Fusion of multi-source precipitation records via coordinate-based generative model Advances in Neural Information Processing Systems36, 288–313 (2023)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.208304Z

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.

Observation 38349aea-8b6b-4a79-a8f8-635a3e005353 · outbound

This paper cites & Daskalakis, C.

Fusion of multi-source precipitation records via coordinate-based generative model & Daskalakis, C

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:07:51.198360Z

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.

Observation 223d49e6-f291-42d7-82b4-f7c08ca347b6 · outbound

This paper cites Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data.

Fusion of multi-source precipitation records via coordinate-based generative model Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.853453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1dafae54-c68b-4bfe-8365-0ffd86a5ea0e · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 85

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.187710Z

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.

Observation a8e3b47a-2f11-4ac6-be70-79da31e6a9a8 · outbound

This paper cites an unresolved cited work.

Fusion of multi-source precipitation records via coordinate-based generative model Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:07:51.176786Z

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.

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