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Paper Citation Record · LEDGER

The ML-EM algorithm in continuum: sparse measure solutions

As of 18 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:1909.01966.

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

pith.paper-citation-record.v1
1909.01966 v2

Coverage vector

measured 40 of 40 reference resolution

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measured 40 of 40 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

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External citation measurements

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Outbound references

Observation d4ba3581-ff88-499e-bb3e-6363c4e76820 · outbound

This paper cites ODL-a Python framework for rapid prototyping in inverse problems.

The ML-EM algorithm in continuum: sparse measure solutions ODL-a Python framework for rapid prototyping in inverse problems

Reference 1

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This paper cites Topics in inverse problems.

The ML-EM algorithm in continuum: sparse measure solutions Topics in inverse problems

Reference 2

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This paper cites Regularization of multiplicative iterative algorithms with nonnegative constraint.

The ML-EM algorithm in continuum: sparse measure solutions Regularization of multiplicative iterative algorithms with nonnegative constraint

Reference 3

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Observation a7459f57-26ad-4750-bc8d-66599e4cf038 · outbound

This paper cites Improved bounds on Bell numbers and on moments of sums of random variables.

The ML-EM algorithm in continuum: sparse measure solutions Improved bounds on Bell numbers and on moments of sums of random variables

Reference 4

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Observation ee2f87bd-34f7-4623-a531-c8ec92e0044f · outbound

This paper cites Introduction to inverse problems in imaging.

The ML-EM algorithm in continuum: sparse measure solutions Introduction to inverse problems in imaging

Reference 5

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This paper cites Convex optimization.

The ML-EM algorithm in continuum: sparse measure solutions Convex optimization

Reference 6

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This paper cites Iterative image reconstruction algorithms based on cross-entropy minimization.

The ML-EM algorithm in continuum: sparse measure solutions Iterative image reconstruction algorithms based on cross-entropy minimization

Reference 7

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Observation 91031b14-d2e6-45f3-86bb-2a1635cd95ba · outbound

This paper cites Iterative image-reconstruction algorithms based on cross-entropy minimization.

The ML-EM algorithm in continuum: sparse measure solutions Iterative image-reconstruction algorithms based on cross-entropy minimization

Reference 8

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Observation a61e9ad1-1baa-4f70-880e-6a1d64ec7334 · outbound

This paper cites Iterative reconstruction algorithms based on cross-entropy minimization.

The ML-EM algorithm in continuum: sparse measure solutions Iterative reconstruction algorithms based on cross-entropy minimization

Reference 9

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This paper cites C., Oberlin, T., Dobigeon, N., Févotte, C., Stute, S., Ribeiro, M.-J., and Tauber, C.

The ML-EM algorithm in continuum: sparse measure solutions C., Oberlin, T., Dobigeon, N., Févotte, C., Stute, S., Ribeiro, M.-J., and Tauber, C

Reference 10

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Observation ef857f04-f81b-4fc8-a1a3-18fc858cbf30 · outbound

This paper cites Information geonetry and alternating minimization procedures.Statistics and decisions 1 (1984), 205–237.

The ML-EM algorithm in continuum: sparse measure solutions Information geonetry and alternating minimization procedures.Statistics and decisions 1 (1984), 205–237

Reference 11

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This paper cites P., Laird, N.

The ML-EM algorithm in continuum: sparse measure solutions P., Laird, N

Reference 12

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This paper cites A., Clinthome, N.

The ML-EM algorithm in continuum: sparse measure solutions A., Clinthome, N

Reference 13

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The ML-EM algorithm in continuum: sparse measure solutions Unresolved cited work

Reference 14

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This paper cites 4DCTimagereconstruction with diffeomorphic motion model.Medical image analysis 16 , 6 (2012), 1307–1316.

The ML-EM algorithm in continuum: sparse measure solutions 4DCTimagereconstruction with diffeomorphic motion model.Medical image analysis 16 , 6 (2012), 1307–1316

Reference 15

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This paper cites M., and Larkin, R.

The ML-EM algorithm in continuum: sparse measure solutions M., and Larkin, R

Reference 16

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The ML-EM algorithm in continuum: sparse measure solutions Unresolved cited work

Reference 17

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This paper cites Lectures on the Poisson process , vol.

The ML-EM algorithm in continuum: sparse measure solutions Lectures on the Poisson process , vol

Reference 19

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The ML-EM algorithm in continuum: sparse measure solutions Unresolved cited work

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This paper cites Positron emission tomography, Borel measures and weak convergence.Inverse Problems 12 , 6 (1996), 965.

The ML-EM algorithm in continuum: sparse measure solutions Positron emission tomography, Borel measures and weak convergence.Inverse Problems 12 , 6 (1996), 965

Reference 21

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The ML-EM algorithm in continuum: sparse measure solutions Concentration Inequalities for the Empirical Distribution

Reference 22

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This paper cites Iterative continuous maximum-likelihood reconstruction method.Mathematical methods in the applied sciences 15 , 4 (1992), 275–286.

The ML-EM algorithm in continuum: sparse measure solutions Iterative continuous maximum-likelihood reconstruction method.Mathematical methods in the applied sciences 15 , 4 (1992), 275–286

Reference 23

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This paper cites On an iterative method for a class of integral equations of the first kind.Mathematical methods in the applied sciences 9 , 1 (1987), 137–168.

The ML-EM algorithm in continuum: sparse measure solutions On an iterative method for a class of integral equations of the first kind.Mathematical methods in the applied sciences 9 , 1 (1987), 137–168

Reference 24

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This paper cites On properties of the iterative maximum likelihood reconstruction method.Mathematical Methods in the Applied Sciences 11 , 3 (1989), 331–342.

The ML-EM algorithm in continuum: sparse measure solutions On properties of the iterative maximum likelihood reconstruction method.Mathematical Methods in the Applied Sciences 11 , 3 (1989), 331–342

Reference 25

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This paper cites Mathematical methods in image reconstruction , vol.

The ML-EM algorithm in continuum: sparse measure solutions Mathematical methods in image reconstruction , vol

Reference 26

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This paper cites Spatiotemporal PET reconstruction using ML-EM with learned diffeomorphic deformation.

The ML-EM algorithm in continuum: sparse measure solutions Spatiotemporal PET reconstruction using ML-EM with learned diffeomorphic deformation

Reference 27

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This paper cites M., and Fessler, J.

The ML-EM algorithm in continuum: sparse measure solutions M., and Fessler, J

Reference 28

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The ML-EM algorithm in continuum: sparse measure solutions Unresolved cited work

Reference 29

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This paper cites Random coding strategies for minimum entropy.IEEE Transactions on Informa- tion Theory 21 , 4 (1975), 388–391.

The ML-EM algorithm in continuum: sparse measure solutions Random coding strategies for minimum entropy.IEEE Transactions on Informa- tion Theory 21 , 4 (1975), 388–391

Reference 30

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This paper cites MLEM Experiment Notebook.

The ML-EM algorithm in continuum: sparse measure solutions MLEM Experiment Notebook

Reference 31

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The ML-EM algorithm in continuum: sparse measure solutions Unresolved cited work

Reference 32

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The ML-EM algorithm in continuum: sparse measure solutions W., and Iusem, A

Reference 33

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The ML-EM algorithm in continuum: sparse measure solutions Unresolved cited work

Reference 34

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This paper cites Functional analysis, second ed.

The ML-EM algorithm in continuum: sparse measure solutions Functional analysis, second ed

Reference 35

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The ML-EM algorithm in continuum: sparse measure solutions Unresolved cited work

Reference 36

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The ML-EM algorithm in continuum: sparse measure solutions A., and V ardi, Y

Reference 37

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This paper cites A smoothed EM approach to indirect estimation problems, with particular reference to stereology and emission tomography.

The ML-EM algorithm in continuum: sparse measure solutions A smoothed EM approach to indirect estimation problems, with particular reference to stereology and emission tomography

Reference 38

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This paper cites A statistical model for positron emission tomogra- phy.

The ML-EM algorithm in continuum: sparse measure solutions A statistical model for positron emission tomogra- phy

Reference 39

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This paper cites Asymptotic approximations of integrals , vol.

The ML-EM algorithm in continuum: sparse measure solutions Asymptotic approximations of integrals , vol

Reference 40

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Pith citing papers

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