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Paper Citation Record · LEDGER

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks

As of 22 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2412.00527.

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

pith.paper-citation-record.v1
2412.00527 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:25:32.805423Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

57 of 57 outbound references displayed

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External citation measurements

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Outbound references

Observation 34dd61a7-0708-4520-8a12-6f2c3406e7f3 · outbound

This paper cites Alessandrini.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Alessandrini

Reference 1

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Observation 69654b7c-9e22-468a-adea-7e58a5854520 · outbound

This paper cites Ammari, J.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Ammari, J

Reference 2

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Observation 8a76c188-24ea-40a3-8203-e254c3fae207 · outbound

This paper cites Ammari, L.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Ammari, L

Reference 3

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Observation aa052fcc-be83-4d4a-9ce7-31006c51a48b · outbound

This paper cites Anthony and P.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Anthony and P

Reference 4

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Observation 526ee504-a02a-465b-b063-33543d096186 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 5

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Observation 85002ad8-f8b8-469e-8e4b-2bcb2bb9148f · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 6

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Observation 9cef2e06-be1f-45ec-97c4-e7e575f7e568 · outbound

This paper cites Bar and N.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Bar and N

Reference 7

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Observation 9d4072b4-84fe-4272-b605-1aa2768ed206 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 8

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Observation 2b09e525-e4a8-4073-800e-13988a67d4e4 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 9

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This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 10

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Observation 4543180b-f561-499e-abb8-9a2fdecfc768 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 11

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Observation b1a05b24-cf61-4fbb-904a-b41397d49e82 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 12

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Observation fc35142d-5c68-4b3e-a0ea-7008fc8a27bb · outbound

This paper cites Let data talk: data-regularized operator learning theory for inverse problems.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Let data talk: data-regularized operator learning theory for inverse problems

Reference 13

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Observation 45476f18-9a5c-4cc0-919b-0c67a843a495 · outbound

This paper cites Deckelnick and M.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Deckelnick and M

Reference 14

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Observation 4917fcb2-1d3c-44f5-8032-9b4c23e4809b · outbound

This paper cites Dolean, A.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Dolean, A

Reference 15

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Observation 1a8bf418-2132-472d-ac3d-1fd9934cf745 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 16

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Observation a372a8d5-2efa-4534-a6be-b8e5e349a134 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 17

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Observation 60c62e02-7cb5-493f-91bb-593f6af1d679 · outbound

This paper cites Grisvard.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Grisvard

Reference 18

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Observation 8e77776d-5efc-4302-949e-3e08b9127b32 · outbound

This paper cites G¨ uhring and M.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks G¨ uhring and M

Reference 19

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Observation 139256a9-e67a-4ace-a0b5-0a115a2b1143 · outbound

This paper cites Guo and J.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Guo and J

Reference 20

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Observation d5a73d3e-9f4a-4529-912c-a9252a282b95 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 21

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 22

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Observation 8f1aceb8-4ec0-45a7-afc1-0e560fa4dd0b · outbound

This paper cites Hoell, A.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Hoell, A

Reference 23

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 24

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 25

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This paper cites Jacot, F.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Jacot, F

Reference 26

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 27

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 28

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 29

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 30

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This paper cites Khoo and L.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Khoo and L

Reference 31

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Observation d8853877-01f5-49e8-8a39-2324690e713e · outbound

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 32

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 33

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Source-reported events for the cited work

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Observation d9672922-8f97-4b2b-85f9-c9b3e781f89f · outbound

This paper cites Krishnapriyan, A.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Krishnapriyan, A

Reference 34

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9b3c6554-6761-42d4-a9fc-9cbf89e6fcf8 · outbound

This paper cites Monard and G.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Monard and G

Reference 37

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.737221Z digest=sha256:5edf6f850690a52660654e2dd3afc3997d0ac5be4b6be6b66a177ba0ba920c50

Observation 3187e717-8264-42e0-ae0e-909180f6f608 · outbound

This paper cites Monard and G.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Monard and G

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:33.065054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.740618Z digest=sha256:45d8dc3ccec74a5fa42b16e8bb8510f1761c1c9c8bab7617143681992a4f5b64

Observation 190ac4e7-ca6a-4901-ad48-5368519a7e82 · outbound

This paper cites Monard and D.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Monard and D

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:33.053507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.744365Z digest=sha256:21b0ed40dc955e4625b92737a664d50cdaf1d60733f5faba41d4e775af3ec07e

Observation befd6a8d-80c6-4a9d-b487-6c7d43259021 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:25:33.041977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a8151bbe-2c36-43a5-ae6e-d42fc3165255 · outbound

This paper cites Nocedal and S.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Nocedal and S

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T05:25:32.753162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:25:32.753162Z digest=sha256:8898ca2364cf73451a3c1672fbff2035ccdf5453d0fc43d684e1c2c0bef1377e

Observation 0d2c1b19-cd3b-465b-87a9-3f2ab43d5272 · outbound

This paper cites Pakravan, P.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Pakravan, P

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:33.022363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.757590Z digest=sha256:74fb06308bfac811b01268439b0c08e888f97183d0e68a29c203c369fa8b41e1

Observation 875c86ea-c0ab-43ca-8734-3eaade9c9c32 · outbound

This paper cites Pokkunuru, P.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Pokkunuru, P

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:33.010926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.761294Z digest=sha256:4c7dce87feaa0669f83f5ee06ccbeb368e9c5c0421cca2fe2a247a629a211c09

Observation 3293fdbe-a5cb-4fcd-b44d-863e5b923e40 · outbound

This paper cites Rahaman, A.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Rahaman, A

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:32.997400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.765609Z digest=sha256:624e2b9a6b376925210deddc22641893f24834f55c4cd5ce6cca322b8ae088a8

Observation 2ea91a5f-74a2-4a90-8f38-af1066888a28 · outbound

This paper cites Raissi, P.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Raissi, P

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:32.985054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.769026Z digest=sha256:6ae8e8a07a63acc016b94d7fa499d738f05d83b3740def4647456b056ea2ced0

Observation 7ea00b94-6417-45c4-b41c-1865254e12fe · outbound

This paper cites Rannacher and B.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Rannacher and B

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:32.972495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.772334Z digest=sha256:689cfe701915e9b935bfa043a0e807ec1a45d7d243378c1deb36171143457c81

Observation 7d35fde6-aaff-43b5-b39e-223d4aac777f · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:25:32.959914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.775520Z digest=sha256:6f26529dafe8c3b0c6855671c2bb72a79d32eea752c39246f96b5fa77c16a722

Observation 1700f0be-0a84-45e0-a643-26abec9f2031 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:25:32.948243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 804b86e2-c760-4d3e-a778-057733f13f85 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-12T05:25:32.781778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:25:32.781778Z digest=sha256:c49033714e344df6e94e204bb2d5a3b8adfce517acad2203eb3b9d1fea54935b

Observation 9b73aa43-888a-47c9-8be4-276266a7ab60 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-12T05:25:32.784637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:25:32.784637Z digest=sha256:53ca4d1cd360288bacff908b1f60e5b21c313da92fafd9a0e90479a1c7650e19

Observation d583ac48-4722-49f5-892d-e46712edc3c6 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T05:25:32.787464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:25:32.787464Z digest=sha256:f7aceefa0e4f4fee56b0007df1474fb4df1e4925fa609226eac905a4d4be1494

Observation 9d18308f-657e-430d-8042-68b37c172a0d · outbound

This paper cites Ulyanov, A.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Ulyanov, A

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:32.911099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.790693Z digest=sha256:d5e47103480e030abde5a8e3833b59f99ed62292b8c7d8a4160fb7cf14e17222

Observation aeffb69a-6e5c-4020-af7b-0f8ca41431d4 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:25:32.899296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.793741Z digest=sha256:4c5262044ed1931e57c58ec3d08ba629068a7929526b34737176d6f984ba7b3c

Observation 8881ee51-5f2e-4bc9-bb0c-2b0f03441f61 · outbound

This paper cites Xu and E.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Xu and E

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:32.887827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.796521Z digest=sha256:e766fb38112bf592ef97308352dd30c0bcea226c022e53a0a5e75db2418724b0

Observation 9c1154db-6065-4560-be98-15f07f7706d7 · outbound

This paper cites Hyper-Parameter Optimization: A Review of Algorithms and Applications.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T05:25:32.799405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:25:32.799405Z digest=sha256:b2b9db15b07a9075a495185c4a3f8ca03ae5f91eab3544cf424167dc2cb06403

Observation d47ab805-7326-4988-923f-6a548f57ded7 · outbound

This paper cites Zhang, Q.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Zhang, Q

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:25:32.876512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.802644Z digest=sha256:badac23993a152809f3a4e7b7688fd02abc0ea237b4a52e8812920a0019edb72

Observation 470540c8-3ee0-4a13-a186-5dd7741be733 · outbound

This paper cites an unresolved cited work.

Imaging Anisotropic Conductivity from Internal Measurements with Mixed Least-Squares Deep Neural Networks Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:25:32.863765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-12T05:25:32.805423Z digest=sha256:4348b822a8f5fc9cc8b2d2358682567be780fa8343e4ec8514881af181f7ab46

Pith citing papers

No inbound Pith citation observations are available.