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Paper Citation Record · LEDGER

Structured Column Subset Selection for Bayesian Optimal Experimental Design

As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2506.00336.

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

pith.paper-citation-record.v1
2506.00336 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:12:25.379633Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:43:07.316694Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 2835f143-7102-47d2-bdb9-22b73fde74db · outbound

This paper cites The European Physical Journal A57(2021) https://doi.org/10.1140/ epja/s10050-021-00382-2.

Structured Column Subset Selection for Bayesian Optimal Experimental Design The European Physical Journal A57(2021) https://doi.org/10.1140/ epja/s10050-021-00382-2

Reference 1

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Observation ae3c4181-05e2-44eb-b4e9-eaf430756518 · outbound

This paper cites Human Brain Mapping8(2-3), 109–114 (1999) https://doi.org/10.1002/(SICI)1097-0193(1999) 8:2/3x109::AID-HBM7y3.0.CO;2-W.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Human Brain Mapping8(2-3), 109–114 (1999) https://doi.org/10.1002/(SICI)1097-0193(1999) 8:2/3x109::AID-HBM7y3.0.CO;2-W

Reference 2

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Observation df379efd-c3f8-4035-bf9f-b5fec282b218 · outbound

This paper cites Magnetic Resonance in Medicine88(1), 239–253 (2022) https://doi.org/10.1002/ mrm.29212 https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.29212.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Magnetic Resonance in Medicine88(1), 239–253 (2022) https://doi.org/10.1002/ mrm.29212 https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.29212

Reference 3

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Observation 73dabfd0-24ec-413f-bfa1-97c9a2d37af3 · outbound

This paper cites Computational Geosciences20, 375–383 (2016).

Structured Column Subset Selection for Bayesian Optimal Experimental Design Computational Geosciences20, 375–383 (2016)

Reference 4

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Observation 856ae3a7-6289-4fb6-85c3-76258a80cddc · outbound

This paper cites Geophysical Jour- nal International236(3), 1309–1331 (2023) https://doi.org/10.1093/gji/ggad492 https://academic.oup.com/gji/article-pdf/236/3/1309/55270901/ggad492.pdf.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Geophysical Jour- nal International236(3), 1309–1331 (2023) https://doi.org/10.1093/gji/ggad492 https://academic.oup.com/gji/article-pdf/236/3/1309/55270901/ggad492.pdf

Reference 5

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Observation c9fde9f9-6dca-40b8-ae3b-3a3c56c65325 · outbound

This paper cites Acta Numerica33, 715–840 (2024) https://doi.org/10.1017/ s0962492924000023.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Acta Numerica33, 715–840 (2024) https://doi.org/10.1017/ s0962492924000023

Reference 6

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Observation 555c8b70-782a-41f3-8ffd-c7c6975e022e · outbound

This paper cites (eds.) The Bayesian Approach to Inverse Problems, pp.

Structured Column Subset Selection for Bayesian Optimal Experimental Design (eds.) The Bayesian Approach to Inverse Problems, pp

Reference 7

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Observation 8b25ae86-091f-493f-8baa-7f4f104d9fa2 · outbound

This paper cites Inverse Problems37(4), 043001 (2021).

Structured Column Subset Selection for Bayesian Optimal Experimental Design Inverse Problems37(4), 043001 (2021)

Reference 8

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Observation 880d3075-6c9f-4a61-8327-530ef10a0fda · outbound

This paper cites Bayesian D-Optimal Experimental Designs via Column Subset Selection.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Bayesian D-Optimal Experimental Designs via Column Subset Selection

Reference 9

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Observation dd665cc1-6a74-41eb-a749-e2244ab0b763 · outbound

This paper cites Statistical Science10(3), 273–304 (1995) https://doi.org/10.1214/ss/1177009939 28.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Statistical Science10(3), 273–304 (1995) https://doi.org/10.1214/ss/1177009939 28

Reference 10

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Observation eb3e8f36-30b6-4254-9e5f-e99a8b500d96 · outbound

This paper cites Acta Numerica29, 403–572 (2020).

Structured Column Subset Selection for Bayesian Optimal Experimental Design Acta Numerica29, 403–572 (2020)

Reference 11

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Observation d7a1ce24-25f6-4012-818d-1e3b98a12d6e · outbound

This paper cites Theoretical Computer Science410(47-49), 4801– 4811 (2009).

Structured Column Subset Selection for Bayesian Optimal Experimental Design Theoretical Computer Science410(47-49), 4801– 4811 (2009)

Reference 12

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Observation 4f9141de-e3f0-49e4-8d08-ac17816336b2 · outbound

This paper cites SIAM Journal on Scientific Computing17(4), 848–869 (1996) https://doi.org/10.1137/0917055.

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Journal on Scientific Computing17(4), 848–869 (1996) https://doi.org/10.1137/0917055

Reference 13

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Observation 0b66dc4d-7525-447b-9dbf-6085331e6773 · outbound

This paper cites SIAM Journal on Matrix Analysis and Applications 37(3), 1223–1249 (2016).

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Journal on Matrix Analysis and Applications 37(3), 1223–1249 (2016)

Reference 14

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Observation 2e897d9a-b5ed-4b50-89f4-2ea173fa3981 · outbound

This paper cites SIAM Journal on Mathemat- ics of Data Science2(1), 189–215 (2020) https://doi.org/10.1137/19M1261043 https://doi.org/10.1137/19M1261043.

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Journal on Mathemat- ics of Data Science2(1), 189–215 (2020) https://doi.org/10.1137/19M1261043 https://doi.org/10.1137/19M1261043

Reference 15

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Observation 0c57a0ec-6876-438b-ab4e-e00428fdc0d8 · outbound

This paper cites Journal of Fluid Mechanics962(2023) https:// doi.org/10.1017/jfm.2023.269.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Journal of Fluid Mechanics962(2023) https:// doi.org/10.1017/jfm.2023.269

Reference 16

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Observation 5ad09bab-5041-411f-a5e5-6c3d9bc7285e · outbound

This paper cites The Annals of Statistics 38(4), 1978–2004 (2010) https://doi.org/10.1214/09-AOS778.

Structured Column Subset Selection for Bayesian Optimal Experimental Design The Annals of Statistics 38(4), 1978–2004 (2010) https://doi.org/10.1214/09-AOS778

Reference 17

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Observation e190e219-5528-4a88-86a7-f5d14c78ee5d · outbound

This paper cites In: Proceedings of the 30th International Conference on Neural Information Processing Systems.

Structured Column Subset Selection for Bayesian Optimal Experimental Design In: Proceedings of the 30th International Conference on Neural Information Processing Systems

Reference 18

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Observation 1b8fcda7-7650-4b67-b0df-da61e17a9fba · outbound

This paper cites Magnetic Resonance in Medicine58(6), 1182–1195 (2007) https://doi.org/10.1002/mrm.21391 https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.21391.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Magnetic Resonance in Medicine58(6), 1182–1195 (2007) https://doi.org/10.1002/mrm.21391 https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.21391

Reference 19

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Observation a4315aed-a712-4271-af1f-da3acd013118 · outbound

This paper cites Investigative Radiology51(6), 349–364 (2016) https://doi.org/10.1097/RLI.0000000000000274.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Investigative Radiology51(6), 349–364 (2016) https://doi.org/10.1097/RLI.0000000000000274

Reference 20

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This paper cites SIAM review 51(3), 455–500 (2009).

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM review 51(3), 455–500 (2009)

Reference 21

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Observation 1a9913e4-2bb4-48a9-b577-4cf466258957 · outbound

This paper cites SIAM Journal on Matrix Analysis and Applications21(4), 1253– 1278 (2000).

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Journal on Matrix Analysis and Applications21(4), 1253– 1278 (2000)

Reference 22

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Observation 334e5887-d2a3-4728-99b3-f9256ac6a43a · outbound

This paper cites SIAM Journal on Sci- entific Computing34(2), 1027–1052 (2012) https://doi.org/10.1137/110836067.

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Journal on Sci- entific Computing34(2), 1027–1052 (2012) https://doi.org/10.1137/110836067

Reference 23

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Observation 246d8861-4b38-411f-b067-dcbff701748b · outbound

This paper cites Experimental design for MRI by greedy policy search.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Experimental design for MRI by greedy policy search

Reference 24

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Observation df467c53-552d-4992-8dec-65073a9ab9b8 · outbound

This paper cites In: 2020 59th IEEE Conference on Decision and Control (CDC), pp.

Structured Column Subset Selection for Bayesian Optimal Experimental Design In: 2020 59th IEEE Conference on Decision and Control (CDC), pp

Reference 25

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This paper cites SIAM Journal on Scientific Computing45(1), 57–77 (2023) https://doi.org/10.1137/21M1466542.

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Journal on Scientific Computing45(1), 57–77 (2023) https://doi.org/10.1137/21M1466542

Reference 26

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Observation 0725333e-0e94-4fd6-8d39-078766b5a299 · outbound

This paper cites Proceedings of the National Academy of Sciences106(3), 697–702 (2009).

Structured Column Subset Selection for Bayesian Optimal Experimental Design Proceedings of the National Academy of Sciences106(3), 697–702 (2009)

Reference 27

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Observation 98d41b37-11e9-4534-b580-d6e3cac423df · outbound

This paper cites SIAM Jour- nal on Scientific Computing38(3), 1454–1482 (2016) https://doi.org/10.1137/ 140978430 https://doi.org/10.1137/140978430.

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Jour- nal on Scientific Computing38(3), 1454–1482 (2016) https://doi.org/10.1137/ 140978430 https://doi.org/10.1137/140978430

Reference 29

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This paper cites Foundations and Trends®in Machine Learning3(2), 123–224 (2011) https://doi.org/10.1561/ 2200000035.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Foundations and Trends®in Machine Learning3(2), 123–224 (2011) https://doi.org/10.1561/ 2200000035

Reference 30

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Observation dab5441e-2db2-4081-96ec-fb064870371a · outbound

This paper cites In: Proceedings of the 33rd International Conference on Interna- tional Conference on Machine Learning - Volume 48.

Structured Column Subset Selection for Bayesian Optimal Experimental Design In: Proceedings of the 33rd International Conference on Interna- tional Conference on Machine Learning - Volume 48

Reference 31

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Observation 836e2e57-f162-43ba-9f24-b648b0a20671 · outbound

This paper cites SIAM Jour- nal on Scientific Computing39(4), 263–291 (2017) https://doi.org/10.1137/ 15M1044680 https://doi.org/10.1137/15M1044680 30.

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Jour- nal on Scientific Computing39(4), 263–291 (2017) https://doi.org/10.1137/ 15M1044680 https://doi.org/10.1137/15M1044680 30

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b2a98f7d-592d-46fc-88fa-7402da2663c3 · outbound

This paper cites Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky

Reference 33

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Observation 77822503-bf75-4aa5-a8d5-6455d0c6090a · outbound

This paper cites SIAM Journal on Matrix Analysis and Applications21(4), 1324–1342 (2000) https://doi.org/10.

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Journal on Matrix Analysis and Applications21(4), 1324–1342 (2000) https://doi.org/10

Reference 34

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a5c2d5e6-7ed8-4719-a18e-3cbb5d667a3f · outbound

This paper cites In: Proceedings of the 2007 SIAM International Conference on Data Mining, pp.

Structured Column Subset Selection for Bayesian Optimal Experimental Design In: Proceedings of the 2007 SIAM International Conference on Data Mining, pp

Reference 35

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 781b8712-ff8a-4c22-820b-5bfd4e279afc · outbound

This paper cites SIAM journal on Optimization23(4), 2037–2060 (2013).

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM journal on Optimization23(4), 2037–2060 (2013)

Reference 36

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d6080470-d481-4eb4-ae0f-6b9a595e86c0 · outbound

This paper cites SIAM Review53(2), 217–288 (2011) https://doi.org/10.1137/090771806 https://doi.org/10.1137/090771806.

Structured Column Subset Selection for Bayesian Optimal Experimental Design SIAM Review53(2), 217–288 (2011) https://doi.org/10.1137/090771806 https://doi.org/10.1137/090771806

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5dacf808-4dd9-4d90-8696-f697f35f860f · outbound

This paper cites an unresolved cited work.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Unresolved cited work

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 91bb9879-6ca8-4eb5-846f-e67790a3cd42 · outbound

This paper cites GAMM- Mitteilungen43(3), 202000014 (2020) https://doi.org/10.1002/gamm.202000014.

Structured Column Subset Selection for Bayesian Optimal Experimental Design GAMM- Mitteilungen43(3), 202000014 (2020) https://doi.org/10.1002/gamm.202000014

Reference 39

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unresolved
no resolver link, observed 2026-08-07T12:12:25.047893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:25.047893Z digest=sha256:13692ad85cf6ba314e4b02be6655b038e805011fccfa32466d179eed9ce2fabd

Observation 6b4dd2ed-01fb-497d-b644-22ea01a70140 · outbound

This paper cites arXiv preprint arXiv:2502.00150 (2025).

Structured Column Subset Selection for Bayesian Optimal Experimental Design arXiv preprint arXiv:2502.00150 (2025)

Reference 40

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verified exact
raw_fallback, observed 2026-08-07T12:12:27.043037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5cf48d8a-748a-40d3-b6b6-fbd0668a0190 · outbound

This paper cites Numerical Algorithms 81(3), 773–811 (2019).

Structured Column Subset Selection for Bayesian Optimal Experimental Design Numerical Algorithms 81(3), 773–811 (2019)

Reference 41

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fd2361f9-8365-4a73-bfa4-ad32882d4a11 · outbound

This paper cites IEEE Transactions on Medical Imaging5, 170–176 (1986).

Structured Column Subset Selection for Bayesian Optimal Experimental Design IEEE Transactions on Medical Imaging5, 170–176 (1986)

Reference 42

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0603a839-1b2e-43cd-b649-bb1139c438b3 · outbound

This paper cites Bridging the Gap Between Deterministic and Probabilistic Approaches to State Estimation.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Bridging the Gap Between Deterministic and Probabilistic Approaches to State Estimation

Reference 43

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c767e443-cffe-43a7-aaea-97cc6222f1f1 · outbound

This paper cites Journal of Atmo- spheric and Oceanic Technology21(10), 1575–1589 (2004) https://doi.org/10.

Structured Column Subset Selection for Bayesian Optimal Experimental Design Journal of Atmo- spheric and Oceanic Technology21(10), 1575–1589 (2004) https://doi.org/10

Reference 44

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Pith citing papers

Observation 293e8c87-b7eb-4821-be19-63f68bd27518 · inbound

Sensor Placement for Tsunami Early Warning via Large-Scale Bayesian Optimal Experimental Design cites this paper.

Sensor Placement for Tsunami Early Warning via Large-Scale Bayesian Optimal Experimental Design Structured Column Subset Selection for Bayesian Optimal Experimental Design

Reference 29

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verified exact
arxiv_id, observed 2026-05-10T16:45:36.457050Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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