Sparse Bayesian Generative Modeling for Compressive Sensing | Paper Citation Record

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This paper cites Eldar and G.

Sparse Bayesian Generative Modeling for Compressive Sensing Eldar and G

Reference 1

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This paper cites Learning fast approximations of sparse coding,.

Sparse Bayesian Generative Modeling for Compressive Sensing Learning fast approximations of sparse coding,

Reference 2

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This paper cites ALISTA: Analytic weights are as good as learned weights in LISTA,.

Sparse Bayesian Generative Modeling for Compressive Sensing ALISTA: Analytic weights are as good as learned weights in LISTA,

Reference 3

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This paper cites Compressed sensing using generative models,.

Sparse Bayesian Generative Modeling for Compressive Sensing Compressed sensing using generative models,

Reference 4

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Observation 43232eae-3fc5-42a3-8612-8d8358992a0d · outbound

This paper cites Deep image prior,.

Sparse Bayesian Generative Modeling for Compressive Sensing Deep image prior,

Reference 5

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This paper cites Deep decoder: Concise image representations from untrained non- convolutional networks,.

Sparse Bayesian Generative Modeling for Compressive Sensing Deep decoder: Concise image representations from untrained non- convolutional networks,

Reference 6

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This paper cites Cryo-care: Content-aware image restoration for cryo-transmission electron microscopy data,.

Sparse Bayesian Generative Modeling for Compressive Sensing Cryo-care: Content-aware image restoration for cryo-transmission electron microscopy data,

Reference 7

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This paper cites Hkf: Hierarchical Kalman filtering with online learned evolution priors for adaptive ECG denoising,.

Sparse Bayesian Generative Modeling for Compressive Sensing Hkf: Hierarchical Kalman filtering with online learned evolution priors for adaptive ECG denoising,

Reference 8

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This paper cites Towards deep learning-aided wireless channel estimation and channel state information feedback for 6G,.

Sparse Bayesian Generative Modeling for Compressive Sensing Towards deep learning-aided wireless channel estimation and channel state information feedback for 6G,

Reference 9

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This paper cites Robust compressed sensing using generative models,.

Sparse Bayesian Generative Modeling for Compressive Sensing Robust compressed sensing using generative models,

Reference 10

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This paper cites Regression shrinkage and selection via the Lasso,.

Sparse Bayesian Generative Modeling for Compressive Sensing Regression shrinkage and selection via the Lasso,

Reference 11

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Observation ff2a9cf9-b24b-4053-a748-43c9345ca6a1 · outbound

This paper cites Optimal tree approximation with wavelets,.

Sparse Bayesian Generative Modeling for Compressive Sensing Optimal tree approximation with wavelets,

Reference 12

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This paper cites Exploiting burst-sparsity in massive MIMO with partial channel support information,.

Sparse Bayesian Generative Modeling for Compressive Sensing Exploiting burst-sparsity in massive MIMO with partial channel support information,

Reference 13

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Observation 67a2bcff-0b75-4200-8ec4-389e41865b72 · outbound

This paper cites Tree-structured compressive sensing with variational Bayesian analysis,.

Sparse Bayesian Generative Modeling for Compressive Sensing Tree-structured compressive sensing with variational Bayesian analysis,

Reference 14

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This paper cites Exploiting structure in wavelet-based Bayesian compressive sensing,.

Sparse Bayesian Generative Modeling for Compressive Sensing Exploiting structure in wavelet-based Bayesian compressive sensing,

Reference 15

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Observation 62f3f79c-9e14-44bb-8c63-a03dac2752e6 · outbound

This paper cites Model-based compressive sensing,.

Sparse Bayesian Generative Modeling for Compressive Sensing Model-based compressive sensing,

Reference 16

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Observation 6fb87c1e-7f90-4036-8a0a-f5b46ddd71fd · outbound

This paper cites Sparse Bayesian learning and the relevance vector machine,.

Sparse Bayesian Generative Modeling for Compressive Sensing Sparse Bayesian learning and the relevance vector machine,

Reference 17

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This paper cites Sparse Bayesian learning for basis selection,.

Sparse Bayesian Generative Modeling for Compressive Sensing Sparse Bayesian learning for basis selection,

Reference 18

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Observation 3ef56bfa-2180-41f5-88f4-e875c804ef72 · outbound

This paper cites Statistical compressed sensing of Gaussian mixture models,.

Sparse Bayesian Generative Modeling for Compressive Sensing Statistical compressed sensing of Gaussian mixture models,

Reference 19

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Observation ce53c238-fb22-470e-8ab5-6e7f8f8ed651 · outbound

This paper cites Reconstruction of signals drawn from a Gaussian mixture via noisy compressive measurements,.

Sparse Bayesian Generative Modeling for Compressive Sensing Reconstruction of signals drawn from a Gaussian mixture via noisy compressive measurements,

Reference 20

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This paper cites Solving inverse problems with piecewise linear estimators: From Gaussian mixture models to structured sparsity,.

Sparse Bayesian Generative Modeling for Compressive Sensing Solving inverse problems with piecewise linear estimators: From Gaussian mixture models to structured sparsity,

Reference 21

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This paper cites Compressive sensing by learning a Gaussian mixture model from measurements,.

Sparse Bayesian Generative Modeling for Compressive Sensing Compressive sensing by learning a Gaussian mixture model from measurements,

Reference 22

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This paper cites Compressive K-SVD,.

Sparse Bayesian Generative Modeling for Compressive Sensing Compressive K-SVD,

Reference 23

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This paper cites Memory and computation efficient PCA via very sparse random projections,.

Sparse Bayesian Generative Modeling for Compressive Sensing Memory and computation efficient PCA via very sparse random projections,

Reference 24

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This paper cites Efficient dictionary learning via very sparse random projections,.

Sparse Bayesian Generative Modeling for Compressive Sensing Efficient dictionary learning via very sparse random projections,

Reference 25

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This paper cites Randnet: Deep learning with compressed measurements of images,.

Sparse Bayesian Generative Modeling for Compressive Sensing Randnet: Deep learning with compressed measurements of images,

Reference 26

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This paper cites K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation,.

Sparse Bayesian Generative Modeling for Compressive Sensing K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation,

Reference 27

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This paper cites AmbientGAN: Generative models from lossy measure- ments,.

Sparse Bayesian Generative Modeling for Compressive Sensing AmbientGAN: Generative models from lossy measure- ments,

Reference 28

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This paper cites Task-aware compressed sensing with generative adversarial networks,.

Sparse Bayesian Generative Modeling for Compressive Sensing Task-aware compressed sensing with generative adversarial networks,

Reference 29

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This paper cites On the Asymptotic Mean Square Error Optimality of Diffusion Models.

Sparse Bayesian Generative Modeling for Compressive Sensing On the Asymptotic Mean Square Error Optimality of Diffusion Models

Reference 30

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This paper cites An asymptotically MSE-optimal estimator based on Gaussian mixture models,.

Sparse Bayesian Generative Modeling for Compressive Sensing An asymptotically MSE-optimal estimator based on Gaussian mixture models,

Reference 31

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This paper cites Leveraging variational autoencoders for parameterized MMSE estimation,.

Sparse Bayesian Generative Modeling for Compressive Sensing Leveraging variational autoencoders for parameterized MMSE estimation,

Reference 32

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 33

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 34

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 35

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This paper cites An introduction to variational autoencoders,.

Sparse Bayesian Generative Modeling for Compressive Sensing An introduction to variational autoencoders,

Reference 36

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This paper cites The perception-distortion tradeoff,.

Sparse Bayesian Generative Modeling for Compressive Sensing The perception-distortion tradeoff,

Reference 37

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This paper cites Prior and posterior networks: A survey on evidential deep learning methods for uncertainty estimation,.

Sparse Bayesian Generative Modeling for Compressive Sensing Prior and posterior networks: A survey on evidential deep learning methods for uncertainty estimation,

Reference 38

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This paper cites Predictive uncertainty estimation via prior networks,.

Sparse Bayesian Generative Modeling for Compressive Sensing Predictive uncertainty estimation via prior networks,

Reference 39

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This paper cites Deep evidential regression,.

Sparse Bayesian Generative Modeling for Compressive Sensing Deep evidential regression,

Reference 40

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This paper cites Gradient-based learning applied to document recognition,.

Sparse Bayesian Generative Modeling for Compressive Sensing Gradient-based learning applied to document recognition,

Reference 41

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This paper cites Adapting to unknown smoothness via wavelet shrinkage,.

Sparse Bayesian Generative Modeling for Compressive Sensing Adapting to unknown smoothness via wavelet shrinkage,

Reference 42

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Observation 166a1f40-b97e-461c-93da-7f0d21c6c1dc · outbound

This paper cites Deep learning face attributes in the wild,.

Sparse Bayesian Generative Modeling for Compressive Sensing Deep learning face attributes in the wild,

Reference 43

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This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Sparse Bayesian Generative Modeling for Compressive Sensing Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 44

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This paper cites Image quality assessment: from error visibility to structural similarity,.

Sparse Bayesian Generative Modeling for Compressive Sensing Image quality assessment: from error visibility to structural similarity,

Reference 45

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This paper cites Adam: A method for stochastic optimization,.

Sparse Bayesian Generative Modeling for Compressive Sensing Adam: A method for stochastic optimization,

Reference 46

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This paper cites Pywavelets: A python package for wavelet analysis,.

Sparse Bayesian Generative Modeling for Compressive Sensing Pywavelets: A python package for wavelet analysis,

Reference 47

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 48

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This paper cites Bickel and K.

Sparse Bayesian Generative Modeling for Compressive Sensing Bickel and K

Reference 49

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This paper cites Scikit-learn: Machine learning in Python,.

Sparse Bayesian Generative Modeling for Compressive Sensing Scikit-learn: Machine learning in Python,

Reference 50

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 51

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 52

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 53

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 54

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Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 55

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Observation ae09adb3-10bc-4cd8-a8bd-52b67cb24827 · outbound

This paper cites (42)) Input: observation y, encoder (µϕ(·), σϕ(·)), decoder γθ(·), meas.

Sparse Bayesian Generative Modeling for Compressive Sensing (42)) Input: observation y, encoder (µϕ(·), σϕ(·)), decoder γθ(·), meas

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:43:30.996225Z

Source-reported events for the cited work

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Observation 9477950d-92c2-4ae5-9766-eb38f924d818 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.865908Z

Source-reported events for the cited work

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Observation 2b53e928-d6db-431a-b10c-2f88838dfb0a · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.850997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3c832d0e-c5eb-40af-ba60-ae113cf01f7f · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.835925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 41783774-43a1-499f-96e0-445abcd38688 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.805120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b5c64e87-0d57-4fca-b85c-918b0509a6ab · outbound

This paper cites (43)) Input: observation y, encoder (µϕ(·), σϕ(·)), decoder γθ(·), meas.

Sparse Bayesian Generative Modeling for Compressive Sensing (43)) Input: observation y, encoder (µϕ(·), σϕ(·)), decoder γθ(·), meas

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:43:30.695735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 87ae42b9-86d1-44d3-955b-3c9494526f10 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 62

Resolution: parse uncertain; raw_fallback, observed 2026-08-12T20:43:30.647428Z

Source-reported events for the cited work

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Observation 166357ca-0faa-49b5-ab29-80bddbe292d1 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.632440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d164f53d-b12b-4d9b-b47f-41da0ef95569 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 64

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.570311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6ad77851-cb71-4f4f-b546-d95660be72d0 · outbound

This paper cites matrix A, dict.

Sparse Bayesian Generative Modeling for Compressive Sensing matrix A, dict

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:43:30.415068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e282a813-5484-4bda-b733-a39f926ed4f0 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.326861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 64437c2c-4962-4434-833a-6631466df3db · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.309663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1b9856bf-df9f-4680-ae75-d752a22112fe · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.199973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6888c131-5f67-458c-9ea0-d9bb45a30323 · outbound

This paper cites (44)) Input: observation y, GMM {ρk, γk}K k=1, meas.

Sparse Bayesian Generative Modeling for Compressive Sensing (44)) Input: observation y, GMM {ρk, γk}K k=1, meas

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:43:30.067695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cd8233db-fb51-4309-91f2-e40575d89478 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.036136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ae6a4c9c-bc3a-41e0-8915-22e7f7ba7671 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:29.931239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fc8b7783-a0fc-408e-8dc1-bacacd5319b8 · outbound

This paper cites (45)) Input: observation y, GMM {ρk, γk}K k=1, meas.

Sparse Bayesian Generative Modeling for Compressive Sensing (45)) Input: observation y, GMM {ρk, γk}K k=1, meas

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:43:29.845708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a2961b64-17aa-4062-8bf8-0477ed9b44b6 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:30.051832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a87edc90-5f94-4907-b347-05d33188d124 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:29.829779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0137d259-9f18-44e0-9875-8b9641e082ed · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 76

Resolution: parse uncertain; raw_fallback, observed 2026-08-12T20:43:29.813813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 15b64a26-b43e-43ce-beb4-4d769f81f460 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:29.796663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation afb04456-4395-4b9c-9c89-7c2bccef5565 · outbound

This paper cites an unresolved cited work.

Sparse Bayesian Generative Modeling for Compressive Sensing Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:43:29.689416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers