Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-28T18:38:46.292829Z
Paper Citation Record · LEDGER
As of 6 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2606.00517.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-28T18:38:46.292829Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
62 of 62 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 7313e340-95de-4701-92d1-34a7901cb16e · outbound
Deep neural network yields regularization for ill-posed inverse problems Springer, New York (1996)
Reference 1
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Observation 15e62e5d-c09c-48ba-bc96-356233044ac5 · outbound
Deep neural network yields regularization for ill-posed inverse problems Springer, New York (2006)
Reference 2
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Observation 1b67381d-dd63-407d-8fcd-977cc763fc5d · outbound
Deep neural network yields regularization for ill-posed inverse problems Walter de Gruyter, Berlin (2012)
Reference 3
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Observation 18f597ca-17a7-4645-aa50-207bd44d7f0d · outbound
Deep neural network yields regularization for ill-posed inverse problems Winston Wiley, Washington, DC New York (1977)
Reference 4
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Observation b5d12bd6-b553-42a7-ae15-35a0e5914cf2 · outbound
Deep neural network yields regularization for ill-posed inverse problems World Scientific, Singapore (2014)
Reference 5
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Observation bb16b114-b02a-4a13-b045-c203663cb794 · outbound
Deep neural network yields regularization for ill-posed inverse problems Inverse Probl.36(5), 055013 (2020)
Reference 6
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Observation b9b0fb1e-1476-4d33-a16b-398f3b0e7061 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 7
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Observation 159028bb-af16-44ff-85ad-4937b7dbeb55 · outbound
Deep neural network yields regularization for ill-posed inverse problems Inverse Probl.39(1), 015007 (2023) 32
Reference 8
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Observation c4dfcf1e-a44f-4b57-b557-39735abcd7ab · outbound
Deep neural network yields regularization for ill-posed inverse problems In: Handbook of Numerical Analysis vol
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Observation 69c44e01-c7d6-4f10-81f5-7c2f019bcaf5 · outbound
Deep neural network yields regularization for ill-posed inverse problems SIAM, Philadelphia (2001)
Reference 10
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Observation ec988541-c08c-4257-8d8b-1f500424d9d0 · outbound
Deep neural network yields regularization for ill-posed inverse problems IEEE Signal Process
Reference 11
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Observation 4ad770d2-4cf0-4e31-9a4a-aae5cf5a03a4 · outbound
Deep neural network yields regularization for ill-posed inverse problems Acta Numer.28, 1–174 (2019)
Reference 12
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Observation b325d38d-f6d3-4d84-8648-1ab1b64d0f70 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 13
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Observation 6b7c76af-c1b9-4fed-9fcd-4e0fe4cbaba7 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 14
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Observation c070626a-b315-4cd7-9937-b1733e819f47 · outbound
Deep neural network yields regularization for ill-posed inverse problems IEEE Trans
Reference 15
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Observation 8782b762-5ef2-48f3-89ce-594bf5b2e27d · outbound
Deep neural network yields regularization for ill-posed inverse problems In: International Conference on Medical Image Computing and Computer-assisted Intervention, pp
Reference 16
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Observation 64fe347c-b8b9-4aef-ace5-69fdbafdd87a · outbound
Deep neural network yields regularization for ill-posed inverse problems IEEE Trans
Reference 17
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Observation 401d3479-e56c-4f92-ae25-2a7441c8862d · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 18
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Observation 6a361ae0-a253-4bd8-9ab8-a358c7389320 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: International Conference on Machine Learning, pp
Reference 19
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Observation 3b8fce4c-a9ef-4a1b-91f3-56c342cfffdb · outbound
Deep neural network yields regularization for ill-posed inverse problems IEEE Trans
Reference 20
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Observation ca356d59-a18c-4301-8dc7-30861672b3ca · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 21
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Observation 3542fa98-f094-45d4-a9af-56178f6f1ef6 · outbound
Deep neural network yields regularization for ill-posed inverse problems Inverse Probl.36(6), 065005 (2020)
Reference 22
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Observation b5f25eaf-85c3-4ecc-ae21-5992aa4cd857 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 23
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Observation 7f9bfa41-c6ac-4443-915b-9aed348f9e86 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision, pp
Reference 24
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Observation e63d0aab-027f-4c86-b520-f83c44d1a087 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp
Reference 25
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Observation da00b709-76bb-4b90-bbde-2029240bfb66 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 26
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Observation edb3b166-563f-4e7c-8f19-e00616733a4a · outbound
Deep neural network yields regularization for ill-posed inverse problems Inverse Probl
Reference 27
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Observation 212370a8-2c16-4ed4-8e68-e7bfd8da6d8f · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 28
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Observation 12c8c8e9-5700-4442-8904-4b8f769bdce1 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 29
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Observation e2080921-3c0b-4176-8c8a-8134162cf2e7 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp
Reference 30
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Observation 4d6824fa-2066-4654-b265-e7b4350f01e2 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: International Conference on Learning Represen- tations (2019)
Reference 31
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Observation dbf6b497-6a17-498b-bb7c-25fb5cce6b3f · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 32
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Observation 2f3825eb-c020-4287-a1bb-05a908d4bbdc · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 33
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Observation f8c8fb81-a857-4262-8055-b2bde4eac139 · outbound
Deep neural network yields regularization for ill-posed inverse problems Transact
Reference 34
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Observation e1e97835-816c-4031-acca-fc2890508a57 · outbound
Deep neural network yields regularization for ill-posed inverse problems IEEE Trans
Reference 35
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Observation a22987f1-6ad9-4402-9602-12de805ee7f3 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 36
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Observation ae8859af-462e-466b-991c-b6d59a248b05 · outbound
Deep neural network yields regularization for ill-posed inverse problems Neural Netw.2(5), 359–366 (1989)
Reference 37
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Observation 49f3e1cb-2c18-4fb9-900b-751b3b854dfe · outbound
Deep neural network yields regularization for ill-posed inverse problems Neural Netw.4(2), 251–257 (1991)
Reference 38
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Observation fe5d6a39-2dab-4d76-811b-0f345835b920 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: International 1989 Joint Conference on Neural Networks, pp
Reference 39
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Observation e5e2eb47-6b30-4f2f-b1cb-9e8aebc554b4 · outbound
Deep neural network yields regularization for ill-posed inverse problems Acta Numer.8, 143–195 (1999)
Reference 40
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Observation fa25d771-7cf8-418c-8051-657f85e5bc26 · outbound
Deep neural network yields regularization for ill-posed inverse problems IEEE Trans
Reference 41
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Observation 577c8904-0082-46fb-9bcc-0f080634f5bd · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 42
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Observation 8f6ded42-7145-423b-839e-54479b1524a7 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 43
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Observation 75aef336-7b31-405e-ba7b-510bf6aa4212 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: Conference on Learning Theory, pp
Reference 44
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Observation 65d70c70-8f5a-42ab-89e3-a0a5a57585e8 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: Conference on Learning Theory, pp
Reference 45
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Observation 0a3805d1-c827-4557-8eca-43d6a9ed9ac0 · outbound
Deep neural network yields regularization for ill-posed inverse problems shallow networks: An approximation theory perspective
Reference 46
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Observation 6f90c598-243f-4455-96ea-b8111ef33b3a · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 47
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Observation aa574b12-35e5-4108-8959-e7328f211491 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 48
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Observation 6a46d184-2200-45b9-8257-2cad4b1abbc6 · outbound
Deep neural network yields regularization for ill-posed inverse problems Neural Netw.94, 103–114 (2017) 35
Reference 49
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Observation ad63c4da-5def-46e3-b45c-6f01dcf12631 · outbound
Deep neural network yields regularization for ill-posed inverse problems In: Conference on Learning Theory, pp
Reference 50
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Observation 52f442be-6adc-48d8-8905-e902b7c7deda · outbound
Deep neural network yields regularization for ill-posed inverse problems Neural Netw.119, 74–84 (2019)
Reference 51
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Observation 88c14ef9-4cd1-422f-8e6b-2f11d61f9ba5 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 52
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Observation 79c4cc83-3e18-4596-9a7b-4abdd8fc6220 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 53
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Observation 3a023a1f-e553-48aa-aff8-7707b8391c60 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 54
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Observation e7eeef34-77dd-4af7-a94d-3371bd23e67b · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 55
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Observation ce2914e6-b56e-45df-8696-6ec68fd4c547 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 56
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Observation 51f58430-a7b0-4426-a831-6e72dbd69768 · outbound
Deep neural network yields regularization for ill-posed inverse problems Neural Netw.154, 152–164 (2022)
Reference 57
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Observation e1b8e0fc-1e64-45d7-8c47-ec4f6735cd8f · outbound
Deep neural network yields regularization for ill-posed inverse problems Neural Netw.108, 296–330 (2018)
Reference 58
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Observation 454cafbc-772e-4b5c-9b60-866dbd6c2d86 · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 59
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Observation 471a932f-d337-4372-9227-5148c09e925c · outbound
Deep neural network yields regularization for ill-posed inverse problems Neural Netw.137, 119–126 (2021)
Reference 60
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Observation f47326a2-c5eb-47ee-a274-4ace697459bb · outbound
Deep neural network yields regularization for ill-posed inverse problems Shallow neural network yields regularization for ill-posed inverse problems
Reference 61
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Observation 7f42ecf5-0bcf-4073-902a-3fecf9656b3b · outbound
Deep neural network yields regularization for ill-posed inverse problems Unresolved cited work
Reference 62
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No inbound Pith citation observations are available.