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Paper Citation Record · LEDGER

Data Depth as a Risk

As of 9 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2507.08518.

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

pith.paper-citation-record.v1
2507.08518 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:27:05.047268Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

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

47 of 47 outbound references displayed

  • verified exact3
  • verified fuzzy21
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 20d68264-0fcf-463c-9b3f-73f9b06ad776 · outbound

This paper cites Latent Space Autoregression for Novelty Detection.

Data Depth as a Risk Latent Space Autoregression for Novelty Detection

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:27:06.178144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:03.859016Z digest=sha256:145248c16f5f80040629e90f859bac560b7699dd603f3bcea5089ebf9631c5b0

Observation e2f8f682-37ac-4c64-906c-70d6c6739369 · outbound

This paper cites Theory of reproducing kernels.

Data Depth as a Risk Theory of reproducing kernels

Reference 2

Resolution
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no resolver link, observed 2026-08-06T18:27:03.936327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:03.936327Z digest=sha256:bdb56248c9259d49505a97d6a9bcf11a1522908df1f3b79e33166bb525ccb796

Observation 29cb305e-c0c0-4d5f-aaf0-17b554ac012d · outbound

This paper cites Learning theory from first principles.

Data Depth as a Risk Learning theory from first principles

Reference 3

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no resolver link, observed 2026-08-06T18:27:03.994964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:03.994964Z digest=sha256:28e42b24feeee774d64f13b206cccecdc394b85f477d8e1e277feee58fec4692

Observation d7259dde-14dc-459d-8b48-179d348b50bd · outbound

This paper cites Bartlett and Shahar Mendelson.

Data Depth as a Risk Bartlett and Shahar Mendelson

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.652295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.031298Z digest=sha256:596d5ef2f3c36539a1cb6672009de9774201912668a58067d2596510907705ab

Observation 4e341e81-9b5f-41cc-ab4b-20ba151abfab · outbound

This paper cites Classification-based anomaly detection for general data.

Data Depth as a Risk Classification-based anomaly detection for general data

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.635955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.111165Z digest=sha256:69afaecc4de9ac9907a5b0174840100a4d5105be38845072487db7669818a330

Observation c9d2b9ee-bf8e-4c99-acc9-0837b6c0cddf · outbound

This paper cites Reproducing kernel Hilbert spaces in probability and statistics.

Data Depth as a Risk Reproducing kernel Hilbert spaces in probability and statistics

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.617799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.221361Z digest=sha256:5d40912e4c321aea4bd433748ec7977bd2df7d0b400077bb6b4adbc43c627299

Observation 1f44b1fa-1b99-4a4f-8e8d-6f7d52963a43 · outbound

This paper cites an unresolved cited work.

Data Depth as a Risk Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T18:27:04.269638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.269638Z digest=sha256:f5526742c9d9af670b19e9c4a0167ee0ba0a5fc07912ac84e77711bb38791112

Observation 0ccee690-e977-46ab-90a7-07186877cac7 · outbound

This paper cites Random rotation ensembles.

Data Depth as a Risk Random rotation ensembles

Reference 8

Resolution
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raw_fallback, observed 2026-08-06T18:27:06.600658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.314497Z digest=sha256:b5aac0746bcbbee57d1a6e2271b321ae7800ebb0110e9e2676bef72c13a399a4

Observation 21f83e8a-14cc-4add-8583-235132a5c173 · outbound

This paper cites Convex Optimization.

Data Depth as a Risk Convex Optimization

Reference 9

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.423024Z digest=sha256:a7b17af336beb9cf56c229e6022307d96f14cdcd10fbffeb82eabb85149eb207

Observation d9c42c3f-c250-43ab-a02c-9cd12ec336f3 · outbound

This paper cites Breunig, Hans-Peter Kriegel, Raymond T.

Data Depth as a Risk Breunig, Hans-Peter Kriegel, Raymond T

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.513014Z digest=sha256:9ddb30665130216413d0115fd4aab8966d0b7bfda5955c5f46da93b3c2a630a8

Observation 233a5b73-d022-4b58-86ad-965bc1d14b2e · outbound

This paper cites Fast kernel half-space depth for data with non-convex supports.

Data Depth as a Risk Fast kernel half-space depth for data with non-convex supports

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:27:05.929992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.560615Z digest=sha256:c0f111f997d2adad1724619c205d77277111bcaca3f46b9a4983670da60c4f3a

Observation f1a3c60c-e9b6-4a67-9883-29bc104f0179 · outbound

This paper cites Beyond mahalanobis distance for textual ood detection.

Data Depth as a Risk Beyond mahalanobis distance for textual ood detection

Reference 12

Resolution
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raw_fallback, observed 2026-08-06T18:27:06.569123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.594716Z digest=sha256:37a899cd3a2767a5e1ba642bf0c23e82e15e72bf8a2447860f016d0ec4698696

Observation 90e18804-29e9-42d1-b08e-38c0d2c82e50 · outbound

This paper cites Handbook of Convergence Theorems for (Stochastic) Gradient Methods.

Data Depth as a Risk Handbook of Convergence Theorems for (Stochastic) Gradient Methods

Reference 13

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T18:27:04.741729Z digest=sha256:c825d9c653f7e7d62525a025d2fb2d476a3fcfe9e53e375833731fef609df97b

Observation 2f21e061-8012-4ee1-bc8e-0910ea33d48f · outbound

This paper cites Deep anomaly detection using geometric transformations.

Data Depth as a Risk Deep anomaly detection using geometric transformations

Reference 14

Resolution
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no resolver link, observed 2026-08-06T18:27:04.860587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.860587Z digest=sha256:9f83ffd9a3fac074973df23a17eeaef1c581a8f69154297334faa35ad9e9a42b

Observation 9bb2f569-626c-46c7-b91c-0dcc86250210 · outbound

This paper cites Borgwardt, Malte J.

Data Depth as a Risk Borgwardt, Malte J

Reference 15

Resolution
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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.866489Z digest=sha256:93a799f80dd1ed9559a20d1701f7cfe9836ae988fa9296ced8a0acdd91b5a9ec

Observation 155e90ff-d8ac-43b1-a742-f2cea98d5fb7 · outbound

This paper cites Faster algorithms for structured linear and kernel support vector machines.

Data Depth as a Risk Faster algorithms for structured linear and kernel support vector machines

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.523093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.872137Z digest=sha256:613d207cdb45f553d35340c59319ff91bc6a12e47875d4ca323fcfe2e1933781

Observation c824a7f8-23fc-4e32-8dff-c75a49984cd3 · outbound

This paper cites Hadsell, S.

Data Depth as a Risk Hadsell, S

Reference 17

Resolution
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no resolver link, observed 2026-08-06T18:27:04.878081Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T18:27:04.878081Z digest=sha256:d13ae46281bf1334750ef1e77bc42b2f649c75ac7da9c8f6c05e1fd4899959dc

Observation 0e6f3811-77fa-4a02-ba9f-66d314bad916 · outbound

This paper cites On the complexity of linear prediction: Risk bounds, margin bounds, and regularization.

Data Depth as a Risk On the complexity of linear prediction: Risk bounds, margin bounds, and regularization

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.505553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.883006Z digest=sha256:80a30770955ae89e881e2e5b885ce24fc62e317e4a7f89ed0e98a32a4db612f6

Observation 7f591dcd-39d8-4bfa-a64b-9933f7adaddc · outbound

This paper cites A new measure of rank correlation.

Data Depth as a Risk A new measure of rank correlation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.487200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.887775Z digest=sha256:6715f58c3b7dc83378842150c3f2b0ac14c54322bed8172745e18395608c3bfd

Observation f88583ad-56d1-41de-ae1a-e190b7b27f96 · outbound

This paper cites Auto-Encoding Variational Bayes.

Data Depth as a Risk Auto-Encoding Variational Bayes

Reference 20

Resolution
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no resolver link, observed 2026-08-06T18:27:04.892900Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T18:27:04.892900Z digest=sha256:420bb6cecec55b89e7af59cb44868000c1fd7dcebeddc35d408ddb7577668d8b

Observation da24d710-43f8-4d86-8a9c-4340140b11a7 · outbound

This paper cites Mnist handwritten digit database.

Data Depth as a Risk Mnist handwritten digit database

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.470813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.898377Z digest=sha256:ddaf19b837fd29d034aa6e666636629b46eda1adecf33d21b8494449ab6fa037

Observation 938c90c5-f5b9-42c3-95f4-1cc83550fbc8 · outbound

This paper cites Model compression for deep neural networks: A survey.

Data Depth as a Risk Model compression for deep neural networks: A survey

Reference 22

Resolution
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no resolver link, observed 2026-08-06T18:27:04.903339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.903339Z digest=sha256:a06b64a79608dd6676f487c399172951bd15763cdd0106f85de417e8e8bc82e7

Observation 2e563e3c-0ebd-4805-9ddf-86901be09ff9 · outbound

This paper cites Risk bounds and calibration for a smart predict-then-optimize method.

Data Depth as a Risk Risk bounds and calibration for a smart predict-then-optimize method

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.451545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.908795Z digest=sha256:9967e789696e2a0420d065ec0e6b2fc0a1be6aeec5aef1dee2cf8b08e48a788b

Observation 35aa8623-f215-4ad5-b959-7c4e27a20928 · outbound

This paper cites Liu and Kesar Singh and.

Data Depth as a Risk Liu and Kesar Singh and

Reference 24

Resolution
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no resolver link, observed 2026-08-06T18:27:04.915399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.915399Z digest=sha256:efcb702623969c4a4fad66e54074a112ca18ce72d8ab9c6d185088ccd3f77610

Observation 75f3a794-b1de-4d20-a2da-88a39c9ee53b · outbound

This paper cites Beyond least-squares: Fast rates for regularized empirical risk minimization through self-concordance.

Data Depth as a Risk Beyond least-squares: Fast rates for regularized empirical risk minimization through self-concordance

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.433857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.921241Z digest=sha256:4b55d9d8fc3663a6e254b47b355070c95e1a73f1c0adba3dff881a0ed6ef874a

Observation 5cd2586f-cb8e-47e5-9db8-9084c211ccb2 · outbound

This paper cites A vector-contraction inequality for rademacher complexities.

Data Depth as a Risk A vector-contraction inequality for rademacher complexities

Reference 26

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no resolver link, observed 2026-08-06T18:27:04.926315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.926315Z digest=sha256:6df9bf3af92cb90e277685686d9a7a99050e4a2ccaec6ba98bec2359a56f0b21

Observation 541ff01f-21fb-4736-a5fe-1bb014936afc · outbound

This paper cites Anomaly detection using data depth: multivariate case.

Data Depth as a Risk Anomaly detection using data depth: multivariate case

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:27:05.625079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.931144Z digest=sha256:2a940489daa3ee325bc036f3400604b4dd33ec9ce3bd1d55c8fe994ff5ebabb3

Observation 1690f67c-500c-4338-8487-d62e412b70f5 · outbound

This paper cites Nonparametric imputation by data depth.

Data Depth as a Risk Nonparametric imputation by data depth

Reference 28

Resolution
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no resolver link, observed 2026-08-06T18:27:04.937207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.937207Z digest=sha256:4c22c0c84d29d42fe0de9f1470d4fe18aaf6b8c857230859ce6734917e02d98d

Observation 079306f6-ec32-42d8-9bc9-b4fd636a9e8e · outbound

This paper cites Combining statistical depth and fermat distance for uncertainty quantification.

Data Depth as a Risk Combining statistical depth and fermat distance for uncertainty quantification

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.415932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.942148Z digest=sha256:25e2185180e7fe30a594cffd9fad09499380b0a31ae2471008b7000c63cb28fe

Observation 86257d6d-33a2-4bca-bb38-dd971a7219b3 · outbound

This paper cites Pedregosa, G.

Data Depth as a Risk Pedregosa, G

Reference 30

Resolution
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no resolver link, observed 2026-08-06T18:27:04.946656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.946656Z digest=sha256:7ebe28d23504958b3edf8528a887a409d0511814b1637c0be5c66d50cadeec36

Observation 537a47a1-9103-4779-9f90-45a5a9a9deae · outbound

This paper cites Ocgan: One-class novelty detection using gans with constrained latent representations.

Data Depth as a Risk Ocgan: One-class novelty detection using gans with constrained latent representations

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T18:27:04.957421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.957421Z digest=sha256:8590f7d5f1a243e5c576cf3506b30b5bc55bfb77a6efd21d6774859608f3c7ef

Observation 93d05f98-4544-4078-992a-eec2d20960f2 · outbound

This paper cites A halfspace-mass depth-based method for adversarial attack detection.

Data Depth as a Risk A halfspace-mass depth-based method for adversarial attack detection

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.387248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.962256Z digest=sha256:bd1a31d11ec2b713e784a7d2cde728f10b1be5c4a96edc31ac3da6e5615b2777

Observation 08e766cd-58c6-46d8-aa42-f08d8474e51e · outbound

This paper cites Outlier detection datasets (odds) library, 2016.

Data Depth as a Risk Outlier detection datasets (odds) library, 2016

Reference 33

Resolution
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raw_fallback, observed 2026-08-06T18:27:06.369762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.968063Z digest=sha256:73b8862921be9cac83760f8afaa8b589064e44b07b4f097effcaf38b1556c173

Observation c6b05da4-ab33-440d-a8d6-9bf8cbfb7a15 · outbound

This paper cites Reid and Robert C.

Data Depth as a Risk Reid and Robert C

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.350058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:04.973675Z digest=sha256:de95bf4e8cd985ea13939b33d8cdf3501d322eb5b89ac2c32db7e460d907137a

Observation c7fbdfef-d48f-45ef-8a64-6b3c9e1bd527 · outbound

This paper cites Deep one-class classification.

Data Depth as a Risk Deep one-class classification

Reference 35

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unresolved
no resolver link, observed 2026-08-06T18:27:04.978736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.978736Z digest=sha256:c77eaece2ac76840822383e060df09b3ba867cb09f50a29180a0fca3488eb34c

Observation 4b51bdbc-64dc-42d2-a1f1-7dd4b3690263 · outbound

This paper cites Waldstein, Ursula Schmidt - Erfurth, and Georg Langs.

Data Depth as a Risk Waldstein, Ursula Schmidt - Erfurth, and Georg Langs

Reference 36

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no resolver link, observed 2026-08-06T18:27:04.983944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.983944Z digest=sha256:5f136a9706ca2d4a599760be325d79ed40d510be470b4a489185ed2066cc6a91

Observation 03996f26-9668-42b2-abe9-c10d6972693a · outbound

This paper cites Platt, John Shawe-Taylor, Alex J.

Data Depth as a Risk Platt, John Shawe-Taylor, Alex J

Reference 37

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no resolver link, observed 2026-08-06T18:27:04.988879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.988879Z digest=sha256:7d18d83ff548943d86c6aec03312582c01c133bcda02b4a1b3e30693c27b09c9

Observation 274e633b-c511-41fc-8294-92431f8135ab · outbound

This paper cites Spearman.

Data Depth as a Risk Spearman

Reference 38

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unresolved
no resolver link, observed 2026-08-06T18:27:04.994936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:04.994936Z digest=sha256:d9c69ecf7d4c341aa19f6d922ee1a6a078da4ae4883655235e0498f26fc02f2d

Observation 636b5172-425a-4478-960b-fa328fb91089 · outbound

This paper cites Support Vector Machines.

Data Depth as a Risk Support Vector Machines

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.309548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:05.000691Z digest=sha256:4d3bf87bea831472a3b5940bb44fcd86bf727b4b18acfd8f04e081cb5583100d

Observation 578cfd97-ccc9-4b18-9161-026f3a649cc7 · outbound

This paper cites Mathematics and the picturing of data.

Data Depth as a Risk Mathematics and the picturing of data

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.294043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:05.005681Z digest=sha256:5f660803c727b419b03fa61f8c2c84460eea59e195203b02ccfac9944dd401e4

Observation 22484230-073c-45e1-ab33-9e07ca0458c1 · outbound

This paper cites Conditional image generation with pixelcnn decoders.

Data Depth as a Risk Conditional image generation with pixelcnn decoders

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.277105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:05.010387Z digest=sha256:070abdb83c25ba7a7d068ffcacc9a93b95bc22a2ca0fec9601c9d254520ba059

Observation 7df70243-8e07-4df3-8cfb-abcd68ae7aa8 · outbound

This paper cites an unresolved cited work.

Data Depth as a Risk Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:27:06.259121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:05.017310Z digest=sha256:fb5f662096b936a1e3c45553b9c1562b165d3d2abd6dd18b98a8fb5cb1c8757c

Observation 05da26d9-b320-4edc-9f4e-08fc818f81ce · outbound

This paper cites Optimal transport: Old and New , volume 338.

Data Depth as a Risk Optimal transport: Old and New , volume 338

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.242651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:05.022829Z digest=sha256:ec165847b8955b04e8ce8d253034cbc3634d145eddb82c6fd33926eb45ba671a

Observation d9ef187f-685f-4ab9-9160-1a4cb7178009 · outbound

This paper cites One-class anomaly detection via novelty normalization.

Data Depth as a Risk One-class anomaly detection via novelty normalization

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T18:27:05.028905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:05.028905Z digest=sha256:5909130d0afaed0c5be46027ba1bdf3346bf42c27c97ab3bb11b9e6cdcd23b3d

Observation 00dcfa3a-95d1-48dc-9c5a-29105e7b479e · outbound

This paper cites Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017.

Data Depth as a Risk Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T18:27:05.034564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:27:05.034564Z digest=sha256:e1046d92f5f3992e5bd13dccc19d456aeed4bbb672c98a5c8255945290ba0e1c

Observation 5cb6ac70-e4ae-4523-89c4-90ac94c4fd5e · outbound

This paper cites Deep structured energy based models for anomaly detection.

Data Depth as a Risk Deep structured energy based models for anomaly detection

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.211968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:05.041333Z digest=sha256:4df902078b809f9fed5d60f6d713d2c64c45032ab08c991513a9faf7b8d0202f

Observation 9f7f2272-4415-4b67-8094-05fe0e1e8183 · outbound

This paper cites Deep autoencoding gaussian mixture model for unsupervised anomaly detection.

Data Depth as a Risk Deep autoencoding gaussian mixture model for unsupervised anomaly detection

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:27:06.195476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T18:27:05.047268Z digest=sha256:d84f5c714d2a14c37dbc297053094d57236abc520bdf2ce574a9c4d7cf3e19e5

Pith citing papers

No inbound Pith citation observations are available.