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Paper Citation Record · LEDGER

Using superpixels for interpretable feature reduction in large 2D diffraction datasets

As of 7 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.13979.

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pith.paper-citation-record.v1
2607.13979 v1

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measured 38 of 38 reference resolution

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Reference resolution

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External citation measurements

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Outbound references

Observation b0cad011-54b0-442b-8b84-ae272239dc02 · outbound

This paper cites Barry and Williams, David B.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Barry and Williams, David B

Reference 1

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This paper cites Microscopy and Microanalysis , year = 2019, month = may, volume = 25, number = 3, pages =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Microscopy and Microanalysis , year = 2019, month = may, volume = 25, number = 3, pages =

Reference 2

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets Unresolved cited work

Reference 3

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets , title =

Reference 4

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets , title =

Reference 5

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This paper cites and Purohit, Prafull and Chamberlain, Darol and Nguyen, Kayla X.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Purohit, Prafull and Chamberlain, Darol and Nguyen, Kayla X

Reference 6

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This paper cites and Eikenberry, E.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Eikenberry, E

Reference 7

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This paper cites Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment , series =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment , series =

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This paper cites Small , year = 2018, volume = 14, number = 46, pages =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Small , year = 2018, volume = 14, number = 46, pages =

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This paper cites Nature Reviews Physics , year = 2021, month = dec, volume = 3, number = 12, pages =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Nature Reviews Physics , year = 2021, month = dec, volume = 3, number = 12, pages =

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets , title =

Reference 11

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This paper cites and Huttenlocher, Daniel P.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Huttenlocher, Daniel P

Reference 12

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This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence , year = 2012, month = nov, volume = 34, number = 11, pages =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets IEEE Transactions on Pattern Analysis and Machine Intelligence , year = 2012, month = nov, volume = 34, number = 11, pages =

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This paper cites and Werbrouck, Andreas and Datta, Amit K.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Werbrouck, Andreas and Datta, Amit K

Reference 14

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This paper cites Journal of Machine Learning Research , year = 2011, volume = 12, number = 85, pages =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Journal of Machine Learning Research , year = 2011, volume = 12, number = 85, pages =

Reference 15

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Lindenstrauss, Joram , title =

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This paper cites Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD'96) , year = 1996, month = aug, pages =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD'96) , year = 1996, month = aug, pages =

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This paper cites Fast 4D-STEM-based phase mapping for amorphous and mixed materials.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Fast 4D-STEM-based phase mapping for amorphous and mixed materials

Reference 18

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This paper cites Strain-driven stabilization of a room-temperature chiral multiferroic with coupled ferroaxial and ferroelectric order.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Strain-driven stabilization of a room-temperature chiral multiferroic with coupled ferroaxial and ferroelectric order

Reference 19

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This paper cites Benjamin and Mendible, Ariana and Wihlborn, Sophie and Kutz, J.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Benjamin and Mendible, Ariana and Wihlborn, Sophie and Kutz, J

Reference 20

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Pekin, Thomas C

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Bedford, Nicholas M

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Bedford, Nicholas M

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets Macromolecules , year = 2006, month = feb, volume = 39, number = 6, pages =

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets Cell , year = 2014, month = nov, volume = 159, number = 5, pages =

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets , title =

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets Journal of Synchrotron Radiation , year = 2024, month = jun, volume = 31, number = 4, pages =

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Ivashko, Oleh and Igoa Salda

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets Journal of Synchrotron Radiation , year = 2021, month = jan, volume = 28, number = 1, pages =

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets and Franz, Hermann , title =

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets Journal of Synchrotron Radiation , year = 2023, month = jul, volume = 30, number = 5, pages =

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Using superpixels for interpretable feature reduction in large 2D diffraction datasets Powder Diffraction , year = 2014, month = dec, volume = 30, number =

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-08-02T03:11:58.856305Z digest=sha256:f2d15f50cb26a7da0fd9b5f47aa225a8821ba4b83f3d744a8a900c015cec44e4

Observation b4f83e1c-617a-4f05-b345-8f05909b7039 · outbound

This paper cites Journal of Synchrotron Radiation , year = 2022, month = jan, volume = 29, number = 1, pages =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Journal of Synchrotron Radiation , year = 2022, month = jan, volume = 29, number = 1, pages =

Reference 37

Resolution
verified exact
doi, observed 2026-08-02T03:13:21.863724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-08-02T03:11:58.859931Z digest=sha256:1471c63841860bae52802f6710d7019fba66624c85f8501d5c22d6d165d9c28a

Observation 5fe92535-d2aa-4cb0-ab9b-2b028c0662b2 · outbound

This paper cites Microscopy and Microanalysis , volume =.

Using superpixels for interpretable feature reduction in large 2D diffraction datasets Microscopy and Microanalysis , volume =

Reference 38

Resolution
verified exact
doi, observed 2026-08-02T03:13:21.659948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-08-02T03:11:58.863279Z digest=sha256:0b74b3c7e06cb6decc17db198d2676a8577406ade3c723da2b6840cb66aa9d4b

Pith citing papers

No inbound Pith citation observations are available.