Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T00:35:48.539098Z
Paper Citation Record · LEDGER
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators
As of 12 August 2026, this Paper Citation Record lists 100 of 103 outbound references and 0 inbound Pith citation observations for arXiv:2608.07630.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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
Reference resolution
100 of 103 outbound references displayed
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- verified fuzzy50
- unresolved45
- parse uncertain0
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 285ad7f3-04ea-4b56-b3ce-bc9f929af09e · outbound
This paper cites International Conference on Artificial Intelligence and Statistics , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators International Conference on Artificial Intelligence and Statistics , pages =
Reference 1
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 349bdff2-27bc-4e4a-8d14-228ab763b81a · outbound
This paper cites International economic review , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators International economic review , pages =
Reference 2
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1a63c2c-fa0f-487e-8cb8-7ab94c020e95 · outbound
This paper cites Journal of Financial Econometrics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Journal of Financial Econometrics , volume =
Reference 3
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4eaffbfc-710b-405e-8ed5-59a8a8e3d8a9 · outbound
This paper cites Econometrica: journal of the Econometric Society , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Econometrica: journal of the Econometric Society , pages =
Reference 4
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation addbda08-2fa9-472b-9843-91213a3e1cbc · outbound
This paper cites 2000 , publisher =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators 2000 , publisher =
Reference 5
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4a0e2ed9-b2fb-4cb0-82fd-d07bedd766fc · outbound
This paper cites Statistical Science , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Statistical Science , volume =
Reference 6
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9b20fb8-d316-486c-8482-4b476e1d5558 · outbound
This paper cites an unresolved cited work.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Unresolved cited work
Reference 7
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 38e98329-497d-41b0-8d03-95300f36cd91 · outbound
This paper cites Advances in neural information processing systems , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Advances in neural information processing systems , volume =
Reference 8
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a09b9438-4094-4122-bede-49e0d863a249 · outbound
This paper cites an unresolved cited work.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Unresolved cited work
Reference 9
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd3ef510-6d34-426f-96d3-0eb68d703bdf · outbound
This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Proceedings of the IEEE conference on computer vision and pattern recognition , pages =
Reference 10
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a65e796a-b81e-4062-a5a0-070aabb4f3d4 · outbound
This paper cites 2009 , publisher =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators 2009 , publisher =
Reference 11
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cb06861-19da-42b2-99c5-e99d6f634752 · outbound
This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Reference 12
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14de77f2-67a3-43ea-a6d3-ffbb159f9705 · outbound
This paper cites A method of solving a convex programming problem with convergence rate O bigl(k\^.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators A method of solving a convex programming problem with convergence rate O bigl(k\^
Reference 13
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ba2b2b72-12c0-4cfb-8e28-4a024626bff0 · outbound
This paper cites Ussr computational mathematics and mathematical physics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Ussr computational mathematics and mathematical physics , volume =
Reference 14
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4c52cb92-12a7-49cf-b7fa-6f53f04c680d · outbound
This paper cites 2005 , url =.
Reference 15
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c2b71110-f927-45ed-b9ea-82c694698e8e · outbound
This paper cites Statistics & Probability Letters , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Statistics & Probability Letters , volume =
Reference 16
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb873c51-d9fd-44ce-a6b1-fae020000456 · outbound
This paper cites Decision Support Systems , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Decision Support Systems , volume =
Reference 17
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 86fe747f-656b-4e7c-afe2-2e65b591d889 · outbound
This paper cites The annals of mathematical statistics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators The annals of mathematical statistics , volume =
Reference 18
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation de6ee7a3-42ae-4bee-a3f3-dc2dd49b9e12 · outbound
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Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators doi:10.5281/zenodo.4532597 , url =
Reference 19
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f14cc402-d0e1-4b45-809f-552ab869e6fd · outbound
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Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Six Lectures on Linearized Neural Networks
Reference 20
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b509a79-607d-472b-a03c-dfd7050af17b · outbound
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Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Journal of statistical software , volume =
Reference 21
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d4c922ca-203f-4f00-9d20-ba7e6a2a2909 · outbound
This paper cites Advances in neural information processing systems , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Advances in neural information processing systems , volume =
Reference 22
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 10d8f271-1f31-4406-af94-7b388f40df8d · outbound
This paper cites an unresolved cited work.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Unresolved cited work
Reference 23
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f983384-2d36-4c3f-b849-27588412d007 · outbound
This paper cites The Annals of Mathematical Statistics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators The Annals of Mathematical Statistics , volume =
Reference 24
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a842b86-895a-4534-868d-014c6075d446 · outbound
This paper cites Metrologia , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Metrologia , volume =
Reference 25
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fd8cecd4-446a-4781-9704-b242a779e8c5 · outbound
This paper cites 1972 , publisher =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators 1972 , publisher =
Reference 26
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 313d3056-1419-40d1-a885-fabe3bf44e93 · outbound
This paper cites Advances in neural information processing systems , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Advances in neural information processing systems , volume =
Reference 27
- Resolution
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Source-reported events for the cited work
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Observation cebe8918-4127-4104-9e8e-8d099903fdec · outbound
This paper cites Advances in neural information processing systems , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Advances in neural information processing systems , volume =
Reference 28
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ca1c4144-7336-44f5-9e1b-23351f03c4de · outbound
This paper cites International conference on machine learning , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators International conference on machine learning , pages =
Reference 29
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a49ce846-e1fc-4f01-ba1c-78f530f6e7f7 · outbound
This paper cites Journal of Applied Statistics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Journal of Applied Statistics , volume =
Reference 30
- Resolution
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Source-reported events for the cited work
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Observation 97644fa3-58a1-4aa4-8808-a4d0c6b8a548 · outbound
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Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators British Journal of Mathematical and Statistical Psychology , volume =
Reference 31
- Resolution
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Source-reported events for the cited work
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Observation 8d6f9c16-4396-4295-aa7c-bda1191217f6 · outbound
This paper cites Biometrika , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Biometrika , volume =
Reference 32
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c696a448-b58e-4394-a05d-bea883b039b6 · outbound
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Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Mathematical programming , volume =
Reference 33
- Resolution
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Observation af2014e0-e797-46fb-b0f0-d610ddc1b992 · outbound
This paper cites Advances in Neural Information Processing Systems , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Advances in Neural Information Processing Systems , volume =
Reference 34
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 786f5f33-ce7c-481e-b2f2-502fd0a32571 · outbound
This paper cites Technometrics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Technometrics , volume =
Reference 35
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d7737565-e287-474c-b949-26949f904866 · outbound
This paper cites Mathematics of computation , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Mathematics of computation , volume =
Reference 36
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation bbc29064-bb8f-4b9b-ac7c-b4a60b41a2e9 · outbound
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Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Studying Large Language Model Generalization with Influence Functions
Reference 37
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Source-reported events for the cited work
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Observation 0fad2d22-f12f-4380-a2dc-6863c35d96c7 · outbound
This paper cites Biometrika , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Biometrika , volume =
Reference 38
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c84d19da-92b1-4353-894b-096fd1014f09 · outbound
This paper cites Biometrika , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Biometrika , volume =
Reference 39
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0085d06e-9456-4f38-8ffa-91b22fada294 · outbound
This paper cites Technometrics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Technometrics , volume =
Reference 40
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 01820ce0-da05-44c3-84f3-3b9e51c970d0 · outbound
This paper cites the Annals of Statistics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators the Annals of Statistics , volume =
Reference 41
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2127df96-e107-4acc-8303-60b82b243229 · outbound
This paper cites Advances in neural information processing systems , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Advances in neural information processing systems , volume =
Reference 42
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0b1f85d2-24c8-4fd8-a1ea-19d96ee23dee · outbound
This paper cites Advances in Neural Information Processing Systems , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Advances in Neural Information Processing Systems , volume =
Reference 43
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 54ed0e9a-d247-479f-b3ab-5257e0cc7ed1 · outbound
This paper cites Biometrics , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Biometrics , pages =
Reference 44
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 018e2d2d-f143-4799-8f9d-7538f16a6ca3 · outbound
This paper cites Neural computation , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neural computation , volume =
Reference 45
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 91d4eeae-b6f2-4235-9779-f8cfc9c9bfb5 · outbound
This paper cites International Conference on Artificial Intelligence and Statistics , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators International Conference on Artificial Intelligence and Statistics , pages =
Reference 46
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ed6aab5b-36e4-4a05-8fe8-339bc993c465 · outbound
This paper cites , title =.
Reference 47
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 6e23be9b-106c-42af-a774-f364b6580aeb · outbound
This paper cites Scaling Down Deep Learning with.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Scaling Down Deep Learning with
Reference 48
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 4a8246e0-2cfa-446b-bb2d-41bcc180d743 · outbound
This paper cites Neural Computation , author =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neural Computation , author =
Reference 49
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b0160f6a-0288-4c36-8125-02ebc778ace9 · outbound
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Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Journal of econometrics , volume =
Reference 50
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 5e5d0679-3c0c-4a26-84be-ba80ca86ce3c · outbound
This paper cites Biometrika , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Biometrika , volume =
Reference 51
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 1d0936bf-9955-47a1-99c4-d3b0f05858ba · outbound
This paper cites Biometrika , volume=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Biometrika , volume=
Reference 52
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation da24d04b-be74-4767-97d9-f423ebcb6422 · outbound
This paper cites Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=
Reference 53
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 4c07cf56-6f79-4d17-82ac-9427525b2220 · outbound
This paper cites The Annals of Statistics , pages=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators The Annals of Statistics , pages=
Reference 54
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7ba6148f-0d0b-46fa-acf6-b328619b620d · outbound
This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Reference 55
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4422aa2-9776-41c7-8a4e-031309c345fd · outbound
This paper cites International Conference on Learning Representations , year=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators International Conference on Learning Representations , year=
Reference 56
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 586af938-1648-4333-8d1a-a0537d4ce125 · outbound
This paper cites Proceedings of the 49th annual meeting of the association for computational linguistics: Human language technologies , pages=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Proceedings of the 49th annual meeting of the association for computational linguistics: Human language technologies , pages=
Reference 57
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14e4a8e4-a2ee-4b34-8404-8156b477653a · outbound
This paper cites The annals of mathematical statistics , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators The annals of mathematical statistics , pages =
Reference 58
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 245488bb-dbef-4abd-804b-5139c1fc7bfb · outbound
This paper cites The Annals of Mathematical Statistics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators The Annals of Mathematical Statistics , volume =
Reference 59
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7577614d-71d5-435a-bb79-d9e6e18d30ed · outbound
This paper cites Food quality and preference , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Food quality and preference , volume =
Reference 60
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation bc6f2045-8aee-4344-95de-6678031b90c5 · outbound
This paper cites The Eleventh International Conference on Learning Representations , year=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators The Eleventh International Conference on Learning Representations , year=
Reference 61
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2f6b55ca-f23e-40ca-9925-1a85e0fc2aea · outbound
This paper cites Breakthroughs in statistics: Methodology and distribution , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Breakthroughs in statistics: Methodology and distribution , pages =
Reference 62
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 3535b446-35c7-4e54-bacd-43df13e3faea · outbound
This paper cites Machine learning , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Machine learning , volume =
Reference 63
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8fca4a39-8a39-4e56-8448-fa59a02d46ff · outbound
This paper cites Neural Networks , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neural Networks , volume =
Reference 64
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b845e468-35b0-4a90-b608-9f306645c989 · outbound
This paper cites International Conference on Machine Learning , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators International Conference on Machine Learning , pages =
Reference 65
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2ec08f46-1c63-4c4c-9a62-bea1a9fd04c3 · outbound
This paper cites Neural Computation , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neural Computation , volume =
Reference 66
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 6f24eaf3-e488-4da5-a79f-1839e015fdf9 · outbound
This paper cites Neural processing letters , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neural processing letters , volume =
Reference 67
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0328345c-fb9b-4fb9-a64a-2052b31412a2 · outbound
This paper cites Sociological Methodology , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Sociological Methodology , volume =
Reference 68
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 379b7a9d-5af8-4e8b-9b48-c4b4ad28779d · outbound
This paper cites Journal of the American statistical association , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Journal of the American statistical association , volume =
Reference 69
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation feeecf9a-3748-489b-bf8f-7641376a62f0 · outbound
This paper cites Hinkley , journal =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Hinkley , journal =
Reference 70
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e608125b-53e2-4308-b58c-37275f168e8b · outbound
This paper cites Journal of the Korean Statistical Society , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Journal of the Korean Statistical Society , volume =
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T00:35:49.360982Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a41c69da-761d-4122-bf7f-48c7c5651029 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Adam: A Method for Stochastic Optimization
Reference 72
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d3e8e8f1-8136-4690-adf6-da387398b63c · outbound
This paper cites The annals of statistics , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators The annals of statistics , volume =
Reference 73
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 74ae1dc9-fbaa-4ee7-81a7-7c542ab0bda3 · outbound
This paper cites What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation , url =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation , url =
Reference 74
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 68d502da-8e3b-40b0-93ab-47a7f55e90ce · outbound
This paper cites Journal of the Royal Statistical Society.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Journal of the Royal Statistical Society
Reference 75
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 20f183d1-4d2c-4d62-b0a0-b6bb7d49e123 · outbound
This paper cites International conference on machine learning , pages =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators International conference on machine learning , pages =
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T00:35:49.301482Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 41f2f89c-9a7a-4cc0-bdaf-6f28837e49fa · outbound
This paper cites An Exact Cholesky Decomposition and the Generalized Inverse of the Variance-Covariance Matrix of the Multinomial Distribution, with Applications , urldate =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators An Exact Cholesky Decomposition and the Generalized Inverse of the Variance-Covariance Matrix of the Multinomial Distribution, with Applications , urldate =
Reference 77
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation da9c9db9-a104-450c-962f-20a4cfe74761 · outbound
This paper cites Advances in neural information processing systems , volume=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Advances in neural information processing systems , volume=
Reference 78
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 27b95333-e30a-4ac6-9efe-e9ddd96888bf · outbound
This paper cites , author=.
Reference 79
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a3d87da3-04e9-4c0d-a488-405dc6c7736c · outbound
This paper cites MAGIC: Near-Optimal Data Attribution for Deep Learning.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators MAGIC: Near-Optimal Data Attribution for Deep Learning
Reference 80
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 498b63f9-5d3d-4be1-bb71-f5b68a0d94db · outbound
This paper cites 2024 , eprint =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators 2024 , eprint =
Reference 81
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 06cbca42-b24c-4d10-a9d7-fb598d6b75bc · outbound
This paper cites an unresolved cited work.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Unresolved cited work
Reference 82
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7d0e2069-c0d9-4449-8749-48ef7985f261 · outbound
This paper cites Conference on learning theory , pages=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Conference on learning theory , pages=
Reference 83
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 20dbd1e4-d0ff-4d30-adc6-f2250448e7ee · outbound
This paper cites Annals of statistics , volume=.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Annals of statistics , volume=
Reference 84
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b71fc13-85e8-4f98-917c-489d67c1f3d7 · outbound
This paper cites An Empirical Study of Example Forgetting during Deep Neural Network Learning.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators An Empirical Study of Example Forgetting during Deep Neural Network Learning
Reference 85
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4104eaf6-5565-4b8e-8cfc-5b3b56781002 · outbound
This paper cites Rescaled Influence Functions: Accurate Data Attribution in High Dimension.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Rescaled Influence Functions: Accurate Data Attribution in High Dimension
Reference 86
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 44a868e0-31c3-44b3-b8eb-50f8cccba7f8 · outbound
This paper cites Neurocomputing , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neurocomputing , volume =
Reference 87
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T00:35:49.184608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f9586b50-dfeb-4842-af03-b528ee679907 · outbound
This paper cites an unresolved cited work.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Unresolved cited work
Reference 88
- Resolution
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- raw_fallback, observed 2026-08-11T00:35:49.167033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 562e18fb-e36a-4ac5-8a71-c774f2b376ff · outbound
This paper cites Stability and.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Stability and
Reference 89
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9d12e4ce-662d-44a6-b944-46fe729b1ec3 · outbound
This paper cites On the mean and variance of the generalized inverse of a singular.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators On the mean and variance of the generalized inverse of a singular
Reference 90
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 60f058a5-c306-4638-ac54-dd6b9d5a2480 · outbound
This paper cites Machine learning , volume =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Machine learning , volume =
Reference 91
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T00:35:49.110565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f8621608-02c9-4dc0-838a-c60235b29083 · outbound
This paper cites The Thirty-ninth Annual Conference on Neural Information Processing Systems , year =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators The Thirty-ninth Annual Conference on Neural Information Processing Systems , year =
Reference 92
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T00:35:49.092628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 5428439f-765b-4095-a2d9-c4abf5fe11f9 · outbound
This paper cites Neural Comput.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neural Comput
Reference 93
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a0986a50-bb5b-4985-a68a-d93347281e4b · outbound
This paper cites Neural Computation , author =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neural Computation , author =
Reference 94
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:35:48.498331Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be9bdf10-923b-49ba-8982-6b8f01a937aa · outbound
This paper cites and Bagdanov, Andrew D.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators and Bagdanov, Andrew D
Reference 95
- Resolution
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- raw_fallback, observed 2026-08-11T00:35:48.890252Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 2105e44f-862b-4adf-affc-f8c95645e4f6 · outbound
This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , author =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Proceedings of the AAAI Conference on Artificial Intelligence , author =
Reference 96
- Resolution
- verified exact
- doi, observed 2026-08-11T00:35:48.673581Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 4d410bc9-1d0a-4d3f-9f14-3a5819aa94c3 · outbound
This paper cites an unresolved cited work.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Unresolved cited work
Reference 97
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T00:35:49.072488Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a03f938f-d20e-4cfd-8d95-3909b18983bf · outbound
This paper cites Neural Networks , author =.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Neural Networks , author =
Reference 98
- Resolution
- verified exact
- doi, observed 2026-08-11T00:35:48.651277Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 632f23b2-0786-4b9f-a2eb-3a72a8a87f5a · outbound
This paper cites Dropout as a.
Reference 99
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-11T00:35:49.054321Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation bfa94014-fd65-4ccf-bd41-f333f8b96a18 · outbound
This paper cites an unresolved cited work.
Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators Unresolved cited work
Reference 100
- Resolution
- unresolved
- raw_fallback, observed 2026-08-11T00:35:49.035730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Pith citing papers
No inbound Pith citation observations are available.