Spatiotemporal Imputation with Graph-Informed Flow Matching | Paper Citation Record

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Spatiotemporal Imputation with Graph-Informed Flow Matching Unresolved cited work

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Spatiotemporal Imputation with Graph-Informed Flow Matching S., Goldstein, M., Boffi, N

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Spatiotemporal Imputation with Graph-Informed Flow Matching Spatio-temporal data mining: A survey of problems and methods

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This paper cites TIDE : Time derivative diffusion for deep learning on graphs.

Spatiotemporal Imputation with Graph-Informed Flow Matching TIDE : Time derivative diffusion for deep learning on graphs

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Spatiotemporal Imputation with Graph-Informed Flow Matching and Santaniello, A

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This paper cites B., Gripon, V., Tang, J., and Ortega, A.

Spatiotemporal Imputation with Graph-Informed Flow Matching B., Gripon, V., Tang, J., and Ortega, A

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Spatiotemporal Imputation with Graph-Informed Flow Matching Unresolved cited work

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This paper cites BRITS : Bidirectional recurrent imputation for time series.

Spatiotemporal Imputation with Graph-Informed Flow Matching BRITS : Bidirectional recurrent imputation for time series

Reference 9

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This paper cites Freeway performance measurement system: Mining loop detector data.

Spatiotemporal Imputation with Graph-Informed Flow Matching Freeway performance measurement system: Mining loop detector data

Reference 10

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This paper cites Filling the g\_ap\_s: Multivariate time series imputation by graph neural networks.

Spatiotemporal Imputation with Graph-Informed Flow Matching Filling the g\_ap\_s: Multivariate time series imputation by graph neural networks

Reference 11

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Spatiotemporal Imputation with Graph-Informed Flow Matching Graph deep learning for time series forecasting

Reference 12

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Spatiotemporal Imputation with Graph-Informed Flow Matching T., and Shah, M

Reference 13

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This paper cites Learning from highly sparse spatio-temporal data.

Spatiotemporal Imputation with Graph-Informed Flow Matching Learning from highly sparse spatio-temporal data

Reference 14

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Spatiotemporal Imputation with Graph-Informed Flow Matching and Nichol, A

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This paper cites Graph signal processing for machine learning: A review and new perspectives.

Spatiotemporal Imputation with Graph-Informed Flow Matching Graph signal processing for machine learning: A review and new perspectives

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This paper cites SAITS : Self-attention-based imputation for time series.

Spatiotemporal Imputation with Graph-Informed Flow Matching SAITS : Self-attention-based imputation for time series

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Spatiotemporal Imputation with Graph-Informed Flow Matching Unresolved cited work

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This paper cites H., Mahmood, A., Garcia-Garcia, B., Thanou, D., and Bouwmans, T.

Spatiotemporal Imputation with Graph-Informed Flow Matching H., Mahmood, A., Garcia-Garcia, B., Thanou, D., and Bouwmans, T

Reference 19

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This paper cites Learning dynamics and heterogeneity of spatial-temporal graph data for traffic forecasting.

Spatiotemporal Imputation with Graph-Informed Flow Matching Learning dynamics and heterogeneity of spatial-temporal graph data for traffic forecasting

Reference 20

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This paper cites Filling the missings: Spatiotemporal data imputation by conditional diffusion.

Spatiotemporal Imputation with Graph-Informed Flow Matching Filling the missings: Spatiotemporal data imputation by conditional diffusion

Reference 21

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This paper cites Denoising diffusion probabilistic models.

Spatiotemporal Imputation with Graph-Informed Flow Matching Denoising diffusion probabilistic models

Reference 22

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Spatiotemporal Imputation with Graph-Informed Flow Matching and Ba, J

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Spatiotemporal Imputation with Graph-Informed Flow Matching u dke, D., Schwinn, L., and G \

Reference 24

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This paper cites Diffusion convolutional recurrent neural network: Data-driven traffic forecasting.

Spatiotemporal Imputation with Graph-Informed Flow Matching Diffusion convolutional recurrent neural network: Data-driven traffic forecasting

Reference 25

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Spatiotemporal Imputation with Graph-Informed Flow Matching Unresolved cited work

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This paper cites PriSTI : A conditional diffusion framework for spatiotemporal imputation.

Spatiotemporal Imputation with Graph-Informed Flow Matching PriSTI : A conditional diffusion framework for spatiotemporal imputation

Reference 27

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This paper cites Flowing from words to pixels: A noise-free framework for cross-modality evolution.

Spatiotemporal Imputation with Graph-Informed Flow Matching Flowing from words to pixels: A noise-free framework for cross-modality evolution

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Spatiotemporal Imputation with Graph-Informed Flow Matching Flow straight and fast: Learning to generate and transfer data with rectified flow

Reference 29

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This paper cites Naomi: Non-autoregressive multiresolution sequence imputation.

Spatiotemporal Imputation with Graph-Informed Flow Matching Naomi: Non-autoregressive multiresolution sequence imputation

Reference 30

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This paper cites See further when clear: Curriculum consistency model.

Spatiotemporal Imputation with Graph-Informed Flow Matching See further when clear: Curriculum consistency model

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This paper cites A spatiotemporal industrial soft sensor modeling scheme for quality prediction with missing data.

Spatiotemporal Imputation with Graph-Informed Flow Matching A spatiotemporal industrial soft sensor modeling scheme for quality prediction with missing data

Reference 32

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Spatiotemporal Imputation with Graph-Informed Flow Matching Learning to reconstruct missing data from spatiotemporal graphs with sparse observations

Reference 33

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Spatiotemporal Imputation with Graph-Informed Flow Matching Graph-based forecasting with missing data through spatiotemporal downsampling

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Spatiotemporal Imputation with Graph-Informed Flow Matching L., Lenssen, J

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Spatiotemporal Imputation with Graph-Informed Flow Matching V., Mohamed, S., and Marwala, T

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Spatiotemporal Imputation with Graph-Informed Flow Matching Spatio-temporal graph scattering transform

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Spatiotemporal Imputation with Graph-Informed Flow Matching R., El-Kadi, A., Masters, D., Ewalds, T., Stott, J., Mohamed, S., Battaglia, P., et al

Reference 38

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Spatiotemporal Imputation with Graph-Informed Flow Matching Time-varying graph signal reconstruction

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Spatiotemporal Imputation with Graph-Informed Flow Matching High-resolution image synthesis with latent diffusion models

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Spatiotemporal Imputation with Graph-Informed Flow Matching I., Chamberlain, B

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Spatiotemporal Imputation with Graph-Informed Flow Matching Deep unsupervised learning using nonequilibrium thermodynamics

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Spatiotemporal Imputation with Graph-Informed Flow Matching A., and Nepomuceno-Chamorro, I

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Spatiotemporal Imputation with Graph-Informed Flow Matching P., Kumar, A., Ermon, S., and Poole, B

Reference 44

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Spatiotemporal Imputation with Graph-Informed Flow Matching Consistency models

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Spatiotemporal Imputation with Graph-Informed Flow Matching S., Chi, E

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Spatiotemporal Imputation with Graph-Informed Flow Matching CSDI : Conditional score-based diffusion models for probabilistic time series imputation

Reference 47

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This paper cites Improving and generalizing flow-based generative models with minibatch optimal transport.

Spatiotemporal Imputation with Graph-Informed Flow Matching Improving and generalizing flow-based generative models with minibatch optimal transport

Reference 48

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Spatiotemporal Imputation with Graph-Informed Flow Matching N., Kaiser, ., and Polosukhin, I

Reference 49

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Spatiotemporal Imputation with Graph-Informed Flow Matching Transformers in time series: A survey

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Spatiotemporal Imputation with Graph-Informed Flow Matching Simplifying graph convolutional networks

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Spatiotemporal Imputation with Graph-Informed Flow Matching Diffusion models: A comprehensive survey of methods and applications

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Spatiotemporal Imputation with Graph-Informed Flow Matching ST-MVL : Filling missing values in geo-sensory time series data

Reference 54

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Spatiotemporal Imputation with Graph-Informed Flow Matching Forecasting fine-grained air quality based on big data

Reference 55

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Spatiotemporal Imputation with Graph-Informed Flow Matching Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 56

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Spatiotemporal Imputation with Graph-Informed Flow Matching and Chi, Eric C

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This paper cites International Conference on Machine Learning , year=.

Spatiotemporal Imputation with Graph-Informed Flow Matching International Conference on Machine Learning , year=

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Spatiotemporal Imputation with Graph-Informed Flow Matching ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , year=

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Spatiotemporal Imputation with Graph-Informed Flow Matching ACM SIGKDD Conference on Knowledge Discovery and Data Mining , year=

Reference 60

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Spatiotemporal Imputation with Graph-Informed Flow Matching Advances in Neural Information Processing Systems , year=

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Spatiotemporal Imputation with Graph-Informed Flow Matching Transportation Research Record , volume=

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Observation 5aa580ed-b41c-42c8-87fd-34d7a39fe493 · outbound

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Observation ce212a7c-3b2f-4ffa-886e-c46576a7c72f · outbound

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Observation c98b2b43-6297-4541-a9d7-298dbb191363 · outbound

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Observation ba9d86fd-0928-497e-81f8-61099efeaf80 · outbound

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Reference 67

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Observation be015ef8-f64d-4fba-9262-eb87fa65c52d · outbound

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Reference 69

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Observation f78c516f-3197-47c1-bfbb-abc565d70f73 · outbound

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Observation fccb6195-1e41-4f67-961f-009cb3c19bbd · outbound

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Observation d41711c9-27d0-4aca-8d86-8592a4b52fcb · outbound

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Reference 72

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Observation 76058b37-e3fa-4e2c-bacb-f18a71c0fe40 · outbound

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Reference 73

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Observation f6ae9903-b0bc-4f27-bbc8-81571a3deaa7 · outbound

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Observation 09473052-45cc-4ac4-8d7a-4f8c8ea4cc29 · outbound

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Reference 75

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Observation d5a2b849-a8e6-4c71-b32d-86fd7dcbbd0d · outbound

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Observation 69a7fe69-e985-4d1d-93aa-86d6531a452a · outbound

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Reference 77

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Observation f3ab7790-f049-45de-81e8-926ff8c90c3c · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching Flow Matching Guide and Code

Reference 78

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Observation 1c6952ef-4c52-4e5e-9650-f38b9af78dd7 · outbound

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Reference 79

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Observation 7c84754a-40e7-410f-be1a-090986289be2 · outbound

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Reference 80

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Observation 47e69c05-e7d0-4b32-a055-9ef72898ff7d · outbound

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Reference 81

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Observation 079c5932-8fc1-428f-830e-312478d34148 · outbound

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Reference 82

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Observation 7292b318-7601-49c5-bad3-5e812aad8a50 · outbound

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Reference 83

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation d1beee8f-0fa4-42af-99ca-dac7d791825a · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching Unresolved cited work

Reference 84

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Observation eb0b1844-b888-4d15-be5b-d187316bccb3 · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching IEEE Transactions on Knowledge and Data Engineering , volume=

Reference 85

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation 4d2ef641-9dec-467e-9820-c4ace5829b2d · outbound

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Reference 86

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Observation 89ed0c3a-fd3c-47c3-bc3b-25e1882b8a79 · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching IEEE Transactions on Pattern Analysis and Machine Intelligence , volume=

Reference 87

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation 78f4e42f-ae18-46e6-b22e-88605aaf2576 · outbound

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Reference 88

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Observation f9c00052-5f69-49de-a3dd-bf1454974d84 · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching BMC Medical Informatics and Decision Making , volume=

Reference 89

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation 956e2722-b19c-4eba-b871-355dc05c36ec · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching Current Science , pages=

Reference 90

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Observation 577074ae-6fbc-4bd9-91c4-d5a722e5935d · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching Time Series Analysis of Irregularly Observed Data , pages=

Reference 91

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation f3cc481b-f022-470b-b695-e9b22ec640b8 · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching IEEE/CVF Conference on Computer Vision and Pattern Recognition , year=

Reference 92

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation 125beb4a-50dd-4f43-adf8-77368515351b · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching IEEE Journal of Selected Topics in Signal Processing , volume=

Reference 93

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation 00ebe70b-6372-4b14-99e9-29df5d6514e4 · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching Reconstruction of time-varying graph signals via

Reference 94

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Observation 280e44ab-e9dc-41fc-9952-9a0cc04f960d · outbound

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Reference 95

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Reference 96

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation 5951b8c1-597e-46f3-aad0-34a45d49357b · outbound

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Reference 97

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Observation 97db04b4-9bfc-4db0-b045-4a530c87331b · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching IEEE Transactions on Knowledge and Data Engineering , volume=

Reference 98

Resolution: unresolved; no resolver link, observed 2026-06-28T02:41:55.647924Z

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Observation 8c314d77-f987-4346-b2aa-e8d76639d030 · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching ACM Computing Surveys , volume=

Reference 99

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Observation ed4717ba-7d2e-45ed-8fd6-79165e2ed41f · outbound

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Spatiotemporal Imputation with Graph-Informed Flow Matching International Conference on Learning Representations , year=

Reference 100

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Pith citing papers