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Paper Citation Record · LEDGER

Deep ReLU networks -- injectivity capacity upper bounds

As of 12 August 2026, this Paper Citation Record lists 91 of 91 outbound references and 1 inbound Pith citation observation for arXiv:2412.19677.

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

pith.paper-citation-record.v1
2412.19677 v1

Coverage vector

measured 91 of 91 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:14:23.176737Z

measured 92 of 92 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:29:20.785752Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

91 of 91 outbound references displayed

  • verified exact9
  • verified fuzzy25
  • unresolved57
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a770206d-6ce1-4a52-877e-2c3b6e3f4936 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:22.819480Z digest=sha256:04d01a5d1e0362746d9bf3ef55b41bb36231ac64ccea67c9c63cea78703bd6a9

Observation 43404026-2514-44b6-bf42-336abdc5492d · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-11T00:14:22.824222Z digest=sha256:225ef86fa13fffeb6dde87cbb817ba12413736b07d30a9d8bde7cf840409ffe3

Observation 88c20d59-bd5c-4974-a03e-6a5a1d257e60 · outbound

This paper cites Alweiss, Y.

Deep ReLU networks -- injectivity capacity upper bounds Alweiss, Y

Reference 3

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source=pdf_text observed=2026-08-11T00:14:22.829017Z digest=sha256:a83275cb0228e92f9ba53381c7d324b9ce7ff04529ce9f1b9b06925a0f7cf727

Observation a23fad05-dbb3-4fe3-b6e9-dcfaa81481e5 · outbound

This paper cites Amelunxen, M.

Deep ReLU networks -- injectivity capacity upper bounds Amelunxen, M

Reference 4

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source=pdf_text observed=2026-08-11T00:14:22.833146Z digest=sha256:e26e6e34e3762798b8e8e32b9b6bc7bf749808f18c12905acef360279ce9ee64

Observation e0e020ab-4fb9-4787-85d1-a160424d2731 · outbound

This paper cites Exact full-RSB SAT/UNSAT transition in infinitely wide two-layer neural networks.

Deep ReLU networks -- injectivity capacity upper bounds Exact full-RSB SAT/UNSAT transition in infinitely wide two-layer neural networks

Reference 5

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local_arxiv, observed 2026-08-11T00:14:23.603442Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.837366Z digest=sha256:ee05fd040a6835a5c7eeb6a0a1f5f3620831bf9fa2afbd64a2c4de6d00115ce1

Observation 3d26e3a6-dd64-40f7-8af7-6be1ca0bb190 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 6

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source=pdf_text observed=2026-08-11T00:14:22.841856Z digest=sha256:7fe241436f70a7cd02307ae37933eb22c3ffed02737232c55445c942123f46ec

Observation 4832a55c-bc56-4623-bb3e-9b3d17af8757 · outbound

This paper cites Aubin, W.

Deep ReLU networks -- injectivity capacity upper bounds Aubin, W

Reference 7

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source=pdf_text observed=2026-08-11T00:14:22.846363Z digest=sha256:5754d4e4c238c3a512d165defa6b6a42cdcd84dfad68dabec9d7e128e6f8e78b

Observation 706f032a-14d3-4fd5-b799-619faa76e62c · outbound

This paper cites Baldassi, E.

Deep ReLU networks -- injectivity capacity upper bounds Baldassi, E

Reference 8

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source=pdf_text observed=2026-08-11T00:14:22.850651Z digest=sha256:fd403de9e27b93dc1c40be779b08f4a07b17e04312d1909bf43a5355a1e42244

Observation 1cb13657-da94-4529-8b78-904525b1a6b2 · outbound

This paper cites Baldi and S.

Deep ReLU networks -- injectivity capacity upper bounds Baldi and S

Reference 9

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source=pdf_text observed=2026-08-11T00:14:22.854784Z digest=sha256:374db438733a4d5d6ddd2c4e93399cba4ca89bd7ae6fc0e56c33c5418617baa3

Observation 34806907-aea5-4857-81f9-7f891ce6d738 · outbound

This paper cites Barkai, D.

Deep ReLU networks -- injectivity capacity upper bounds Barkai, D

Reference 10

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source=pdf_text observed=2026-08-11T00:14:22.859006Z digest=sha256:0309a8388a1fe8193898b7c45d5905d347d9edaad175ec283e1aff059c597f0c

Observation 90aff830-0aa6-4f79-b35d-4a9dd51a8994 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 11

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source=pdf_text observed=2026-08-11T00:14:22.862989Z digest=sha256:fb0f4e444e88222ae40a5e712c145649e68a6e25f1f9eec9436a9551b941b22f

Observation 7e9f4a10-e239-4006-a2f3-1b7d8923bfbb · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-11T00:14:22.866664Z digest=sha256:a0660cb24769d1dba82f58c0efdb4eb7174b16bc27eb20019c5a61266e7d23b8

Observation fd267886-70b8-401b-a5ed-b4c3f9b3ee9c · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 13

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Observation 9b89e8ee-3f7e-4eef-9dd3-f48a0ecb23e4 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 14

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Observation 35088075-3acc-40b9-ae82-a4a45b8d73e8 · outbound

This paper cites Daskalakis, D.

Deep ReLU networks -- injectivity capacity upper bounds Daskalakis, D

Reference 15

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Observation fbcea610-7aef-488c-92e2-1314470921a7 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 16

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Observation b0adecfe-3748-4e4e-b7c3-8db562b489a6 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 17

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source=pdf_text observed=2026-08-11T00:14:22.884538Z digest=sha256:3b98b7804208723350eed8cf570c466e2a95d068c7621c6d5c05de8dc38074fd

Observation 961d5789-2386-4c69-a879-f6271a8a5f04 · outbound

This paper cites Engel, H.

Deep ReLU networks -- injectivity capacity upper bounds Engel, H

Reference 18

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source=pdf_text observed=2026-08-11T00:14:22.888271Z digest=sha256:8af4d0fdc05b765a4b248c5f08a0c77a3679a091468a2751b51c0559dc1e0e8a

Observation 8dce4c42-c0d2-4d71-a074-070cc1b76dad · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 19

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source=pdf_text observed=2026-08-11T00:14:22.892436Z digest=sha256:7bb6996aa843ee6c602024a9306d2eefab37570e0d30f2e1eb941f53a4401b55

Observation af7b5a30-a18c-400c-a7ba-296d15a96aae · outbound

This paper cites Fazlyab, A.

Deep ReLU networks -- injectivity capacity upper bounds Fazlyab, A

Reference 20

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source=pdf_text observed=2026-08-11T00:14:22.896427Z digest=sha256:0d095e16278984fe1e3925e183bb739883b339c9cc96026848bf8dcf244837ae

Observation 99ae3fac-9286-445f-a752-317ea8d2221f · outbound

This paper cites Fletcher, Sundeep Rangan, and Philip Schnite r.

Deep ReLU networks -- injectivity capacity upper bounds Fletcher, Sundeep Rangan, and Philip Schnite r

Reference 21

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source=pdf_text observed=2026-08-11T00:14:22.900311Z digest=sha256:45f59ddfdb45a1def8cdfc29c85b9f9a238e9bb1348b345b69d81a0e7825197b

Observation 6e09a92c-84e1-445d-8ffd-df141e671e1a · outbound

This paper cites Franz, G.

Deep ReLU networks -- injectivity capacity upper bounds Franz, G

Reference 22

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Observation d57eef86-c6b4-471c-9b05-d1709abf46c7 · outbound

This paper cites Furuya, M.

Deep ReLU networks -- injectivity capacity upper bounds Furuya, M

Reference 23

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source=pdf_text observed=2026-08-11T00:14:22.908050Z digest=sha256:ee0109211a451d6ad292c7e615bbb9afb7da89bf3a203e3860acc9e3ffdbfda9

Observation 08af7588-272e-49f8-aa2a-e4f6d11e206b · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 24

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Observation 3d00cd9b-d626-45c3-a3bd-8e7fb0ba26d8 · outbound

This paper cites Kizildag, Will Perkins, and Cha ngji Xu.

Deep ReLU networks -- injectivity capacity upper bounds Kizildag, Will Perkins, and Cha ngji Xu

Reference 25

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Observation c6f67bc3-53e6-4cfd-b807-abf75ebcbbe7 · outbound

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Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 26

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source=pdf_text observed=2026-08-11T00:14:22.919204Z digest=sha256:077e970028960b68e35f0c83e0b0a8ecab800906832230b153545ddeb4a09a3b

Observation ef2ab17d-1255-4f2c-a3ae-452128158892 · outbound

This paper cites Gardner and B.

Deep ReLU networks -- injectivity capacity upper bounds Gardner and B

Reference 27

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source=pdf_text observed=2026-08-11T00:14:22.923515Z digest=sha256:be149e263368caecc4df1623936e48aa0e975d1b87c335cd9440fa69d1146c1e

Observation 5d91abc1-8b40-455a-85f2-d8b4d333ca6d · outbound

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Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-11T00:14:22.927044Z digest=sha256:3a0eceee724e3bd80f2c8b34ffca3b0be652ddd34d51c08f27e3f2443207ab7b

Observation 003f7588-f8f6-4a7a-a7ef-21a3efcb4fb3 · outbound

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Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 29

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Observation 84179fe1-7a01-416b-8984-5e42d05ad5e9 · outbound

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Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 30

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source=pdf_text observed=2026-08-11T00:14:22.934540Z digest=sha256:01b0a827a6b7fd5b97c98efffb2363b72783b9dedfcdabc0f92d6cd5a3cfec5b

Observation abc2c280-4c97-460d-af4b-96545e38a383 · outbound

This paper cites Gutfreund and Y.

Deep ReLU networks -- injectivity capacity upper bounds Gutfreund and Y

Reference 31

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source=pdf_text observed=2026-08-11T00:14:22.938691Z digest=sha256:cd65ff520d1e6fbd9d737b02297fc857215c8c5d714ca4a81bf5d013809977f1

Observation d6a0bf0f-1a0a-4540-8d30-276e5e21e201 · outbound

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Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 32

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source=pdf_text observed=2026-08-11T00:14:22.942401Z digest=sha256:c6e951db14a4112ef6d52793c2f409169bf734535e686558de5f99427eb72309

Observation 7c48dd85-90e9-48f7-8f1f-0383ec328be9 · outbound

This paper cites He, C.-K.

Deep ReLU networks -- injectivity capacity upper bounds He, C.-K

Reference 33

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source=pdf_text observed=2026-08-11T00:14:22.946094Z digest=sha256:041f439a1bc4b8e264b36ef5e0b08d66a1ba3b9621f05cbd80ee1e5c52f56ebe

Observation 03d94aa3-1a91-4d93-a3f0-bb1f3417e6de · outbound

This paper cites Rate-Optimal Denoising with Deep Neural Networks.

Deep ReLU networks -- injectivity capacity upper bounds Rate-Optimal Denoising with Deep Neural Networks

Reference 34

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local_arxiv, observed 2026-08-11T00:14:23.581699Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.949670Z digest=sha256:710d6cc7a3c9e7a81ccb9408404d62ffd8c76f9ad5abb7f4f4367ed7dff1482b

Observation 1a1b4355-9227-4eae-bcb8-8580a9c073a1 · outbound

This paper cites Hegde, M.

Deep ReLU networks -- injectivity capacity upper bounds Hegde, M

Reference 35

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source=pdf_text observed=2026-08-11T00:14:22.953868Z digest=sha256:40286c83dc2c0e5bf5b2b5c529770345e9685d08e42d32861d8be4a35c3f63dd

Observation 3f83e9ac-7dab-4dc7-969b-2072a75a13c3 · outbound

This paper cites A Provably Convergent Scheme for Compressive Sensing under Random Generative Priors.

Deep ReLU networks -- injectivity capacity upper bounds A Provably Convergent Scheme for Compressive Sensing under Random Generative Priors

Reference 36

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source=pdf_text observed=2026-08-11T00:14:22.957677Z digest=sha256:7435a603fc3acfb0f0159bb9d9837cb6b836ff3596e7fd125b1143729e742cef

Observation fe84d51d-7546-4b19-8b9c-08af748fce02 · outbound

This paper cites Jordan and A.

Deep ReLU networks -- injectivity capacity upper bounds Jordan and A

Reference 37

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source=pdf_text observed=2026-08-11T00:14:22.962229Z digest=sha256:955d29602134cf0900667d390e5bbf7e9160ad145610a01c8d6fc0cf4c50062f

Observation 35f04020-e5f7-40f0-a45d-138766d4c0c3 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 38

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source=pdf_text observed=2026-08-11T00:14:22.966402Z digest=sha256:d87f6a51be908a2b313fe989b4a398167f5dbc7577e74759df47276e310ff1f8

Observation 042f17f6-24e6-411f-9286-54df91b11bd1 · outbound

This paper cites Kothari, A.

Deep ReLU networks -- injectivity capacity upper bounds Kothari, A

Reference 39

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raw_fallback, observed 2026-08-11T00:14:24.001013Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.970297Z digest=sha256:6189369912f73c9b2ed77fc0e96ad36f27ab88e032f7b0125ff504052e8f0753

Observation 8fa0e912-e8c0-4155-9bea-79aaf7fbc421 · outbound

This paper cites Krauth and M.

Deep ReLU networks -- injectivity capacity upper bounds Krauth and M

Reference 40

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raw_fallback, observed 2026-08-11T00:14:23.985470Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.974034Z digest=sha256:3a6866603e4069d530c9f1796080ad27f1b9e52031484ec34ce5abecdf81d32f

Observation 2e9fdef5-db79-40e2-841a-9d2fd758c731 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 41

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.977753Z digest=sha256:5d4660d1b035ea7cffd2f80d59411ebcb9befe657ba958b51a8ca4752150d8f2

Observation 7a39be40-7c36-4fe6-8e14-4961e16d527f · outbound

This paper cites A Random Matrix Approach to Neural Networks.

Deep ReLU networks -- injectivity capacity upper bounds A Random Matrix Approach to Neural Networks

Reference 42

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source=pdf_text observed=2026-08-11T00:14:22.981694Z digest=sha256:d6a3c91ef66133200ae14d8568ad56184965dc1c0fa872ec52579b05bea1d11b

Observation 739af28b-ce7c-4e09-b9d6-794e5867bd62 · outbound

This paper cites Injectivity of ReLU networks: perspectives from statistical physics.

Deep ReLU networks -- injectivity capacity upper bounds Injectivity of ReLU networks: perspectives from statistical physics

Reference 43

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local_arxiv, observed 2026-08-11T00:14:23.532940Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.985685Z digest=sha256:135ccb1af244bb1f025b9fda6f7f6c8134774aece706650270221c88ab12c5e7

Observation 606e3889-e7ce-427d-8029-c26a68a105f7 · outbound

This paper cites Mardani, Q.

Deep ReLU networks -- injectivity capacity upper bounds Mardani, Q

Reference 44

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raw_fallback, observed 2026-08-11T00:14:23.957251Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.989404Z digest=sha256:013e71f1d854a557f7a98d7fcd790e1dc95fd398cd6142cdaa56e35f14cdcce8

Observation 89578b60-d964-489e-b98f-ba935c637d36 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 45

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raw_fallback, observed 2026-08-11T00:14:23.942999Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.993553Z digest=sha256:d30cf84fe1071367e78346097fbc373df890414f51a948b73213043258e39735

Observation 46deb051-3caa-4030-b7b6-b43682b39601 · outbound

This paper cites Pennington and P.

Deep ReLU networks -- injectivity capacity upper bounds Pennington and P

Reference 46

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raw_fallback, observed 2026-08-11T00:14:23.929871Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:22.997248Z digest=sha256:b7909780911ed4019ce6cb137583191b0f4b806a14f230b38f2e772a843f348d

Observation 2cc6cc82-fb2c-405f-8097-d101464f9485 · outbound

This paper cites Perkins and C.

Deep ReLU networks -- injectivity capacity upper bounds Perkins and C

Reference 47

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source=pdf_text observed=2026-08-11T00:14:23.001293Z digest=sha256:7ea7fcf3e9971db81336f129dd0f3b4d81092c3d9a4fd971d4bd4e9aa6061a46

Observation 1da87fcd-50e3-4fcd-bf97-5d13f6658fdc · outbound

This paper cites Puthawala, K.

Deep ReLU networks -- injectivity capacity upper bounds Puthawala, K

Reference 48

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raw_fallback, observed 2026-08-11T00:14:23.906941Z

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source=pdf_text observed=2026-08-11T00:14:23.004926Z digest=sha256:9d8b27e8844a53d7da65cabfc853b29a419d29dd4fa812b3b9cbc9b6245092ad

Observation 9ba0da82-0a44-43ca-9c5f-f64a3e13006e · outbound

This paper cites Puthawala, M.

Deep ReLU networks -- injectivity capacity upper bounds Puthawala, M

Reference 49

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raw_fallback, observed 2026-08-11T00:14:23.893652Z

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source=pdf_text observed=2026-08-11T00:14:23.008650Z digest=sha256:28bb6d5dbbb0b45bb2270bafbb410e07ca3178a8a9d708379a0c3649b0d0ad65

Observation bdb1fb6f-9dd2-4516-9a12-f1ab70bbfd27 · outbound

This paper cites Rangan, P.

Deep ReLU networks -- injectivity capacity upper bounds Rangan, P

Reference 50

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raw_fallback, observed 2026-08-11T00:14:23.880382Z

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source=pdf_text observed=2026-08-11T00:14:23.012326Z digest=sha256:254c7119f7a3e101dd2446d98e14655b1dfd46b8139ce2f3d933c4467c58b0c1

Observation 47191eb8-7b28-49a0-ad5f-36e4f119da91 · outbound

This paper cites Romano, M.

Deep ReLU networks -- injectivity capacity upper bounds Romano, M

Reference 51

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raw_fallback, observed 2026-08-11T00:14:23.867230Z

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source=pdf_text observed=2026-08-11T00:14:23.016188Z digest=sha256:c33a19a7f2f48cef48a45d07041dff6910650e639de5a9f135394a894862ac89

Observation a12ca419-e329-45c4-8c10-06781e078871 · outbound

This paper cites Leigh Ross and J.

Deep ReLU networks -- injectivity capacity upper bounds Leigh Ross and J

Reference 52

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raw_fallback, observed 2026-08-11T00:14:23.853640Z

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source=pdf_text observed=2026-08-11T00:14:23.019903Z digest=sha256:e01d95dd6d93b1ea1a6b3f93e06a155922e03357b1f44c6f778d13e69fcb45e8

Observation 765f2647-aaf5-47c0-8b00-6c2e322f40a6 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 53

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.023507Z digest=sha256:f6633299a5f1e2c9819807c81bbb33fa0820d782cca29f8cd91511d7f904c3af

Observation 02eaf810-08c4-4a50-8ffc-e4ffe3f53080 · outbound

This paper cites Schneider and W.

Deep ReLU networks -- injectivity capacity upper bounds Schneider and W

Reference 54

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verified fuzzy
raw_fallback, observed 2026-08-11T00:14:23.825243Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.027087Z digest=sha256:0c0c4f4643405ca8b3966fe66e137c76e90ca30e5b60583b171d133e44a1922a

Observation 8a0b24b0-8156-4061-88c5-824d33914c51 · outbound

This paper cites Schniter, S.

Deep ReLU networks -- injectivity capacity upper bounds Schniter, S

Reference 55

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verified fuzzy
raw_fallback, observed 2026-08-11T00:14:23.811901Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.030549Z digest=sha256:542ff41965a6bd219b9fc4cfdb80240126099050c00bdb43ebc065c8acc25198

Observation 41ea093f-3b57-4452-87be-17e9615efa26 · outbound

This paper cites Shah and C.

Deep ReLU networks -- injectivity capacity upper bounds Shah and C

Reference 56

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raw_fallback, observed 2026-08-11T00:14:23.798476Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.034545Z digest=sha256:c10f4a6bddeda6e45bbea47479495f528a6c4b4ddd0f829a283c467621535410

Observation d9b11198-e1bd-45e0-a3cc-78d365bb4606 · outbound

This paper cites Shcherbina and B.

Deep ReLU networks -- injectivity capacity upper bounds Shcherbina and B

Reference 57

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raw_fallback, observed 2026-08-11T00:14:23.785252Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.038045Z digest=sha256:1f6a2c87553ec5715ade570c69dc6c080b6907ac94a6faa469670d57fd1c3c83

Observation 76ac3b10-fabf-46ca-bff1-059b5499265a · outbound

This paper cites Shcherbina and B.

Deep ReLU networks -- injectivity capacity upper bounds Shcherbina and B

Reference 58

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no resolver link, observed 2026-08-11T00:14:23.041368Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T00:14:23.041368Z digest=sha256:27b8110100ae132e66740375de0d6c7d34ba16935785521542c89244ec1fbb0c

Observation 502dd818-1f63-4f29-9269-48fd4f771fd7 · outbound

This paper cites Block-length dependent thresholds in block-sparse compressed sensing.

Deep ReLU networks -- injectivity capacity upper bounds Block-length dependent thresholds in block-sparse compressed sensing

Reference 59

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local_arxiv, observed 2026-08-11T00:14:23.510271Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.045054Z digest=sha256:3cf827b2a5220ce739a0bff2c2fb868ee7ea6e97705be06ca8677a7c294a1d03

Observation 9f5b1ad6-365c-4664-860b-c634d614883f · outbound

This paper cites Various thresholds for $\ell_1$-optimization in compressed sensing.

Deep ReLU networks -- injectivity capacity upper bounds Various thresholds for $\ell_1$-optimization in compressed sensing

Reference 60

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source=pdf_text observed=2026-08-11T00:14:23.049149Z digest=sha256:4a737790cfc2742ddbbf6a37e5502d4a530faf4538df2132586b0e7d2250f4bd

Observation 4977795d-31d2-4aa9-8d56-4b0ae90171d8 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 61

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.053315Z digest=sha256:10467930a58578957cd7e1e3c55ffae9d60600f8d69711a1f03bfbba0c6884c6

Observation d6785f24-a2f6-449e-beac-ec8e2290c60d · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 62

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.056818Z digest=sha256:d3f9953f455b87e595a50a2298d0d06653a661f1c4cdd4dbc66a079f716c296b

Observation c8cd031b-28bc-4979-9a6a-91e73d98d1b1 · outbound

This paper cites Another look at the Gardner problem.

Deep ReLU networks -- injectivity capacity upper bounds Another look at the Gardner problem

Reference 63

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T00:14:23.060501Z digest=sha256:4bc70d3c9ac6b6b75706435ea81785584a55acf2697b60a9337195e78c823b0e

Observation 04ca195f-ad4f-4099-a478-0c7ba24d793e · outbound

This paper cites On the Computing of the Minimum Distance of Linear Block Codes by Heuristic Methods.

Deep ReLU networks -- injectivity capacity upper bounds On the Computing of the Minimum Distance of Linear Block Codes by Heuristic Methods

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.064423Z digest=sha256:928e0f24f91bd51fcc8db175259a1dd5c1eeae01bc53149d185da9f5a4cad48f

Observation dd81d6d2-602a-4995-922c-8e07d1b13b59 · outbound

This paper cites Lifting $\ell_1$-optimization strong and sectional thresholds.

Deep ReLU networks -- injectivity capacity upper bounds Lifting $\ell_1$-optimization strong and sectional thresholds

Reference 65

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local_arxiv, observed 2026-08-11T00:14:23.447042Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T00:14:23.068898Z digest=sha256:cf4a65576617e83c234a861870c793edfe06f0b9a1ca70e084767b342dc42032

Observation 2eeaa5c3-7d97-461c-8dc1-e44a701c55a5 · outbound

This paper cites Lifting/lowering Hopfield models ground state energies.

Deep ReLU networks -- injectivity capacity upper bounds Lifting/lowering Hopfield models ground state energies

Reference 66

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source=pdf_text observed=2026-08-11T00:14:23.072639Z digest=sha256:5e7af469599d29a5e6254a6bbe0fd0e0ed3fd33c828774229acdbe510a5aeb12

Observation 5028a117-9780-4634-bfa0-e416b04f80f2 · outbound

This paper cites Meshes that trap random subspaces.

Deep ReLU networks -- injectivity capacity upper bounds Meshes that trap random subspaces

Reference 67

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source=pdf_text observed=2026-08-11T00:14:23.076730Z digest=sha256:bfc32f31f0ad7a6cdf25fb7bceb91c0f10769f7cf82570dc49a79465f1602b67

Observation cbfbb468-2aef-4287-83c5-b35204578b0b · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 68

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.080573Z digest=sha256:9b77eb4c78a5e80e76451963bbdec72d8226bf26dd91244ad94a92c84c815eda

Observation bc93a770-2cb1-4ffa-b4e6-2f589b3572c7 · outbound

This paper cites Regularly random duality.

Deep ReLU networks -- injectivity capacity upper bounds Regularly random duality

Reference 69

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.084277Z digest=sha256:4d916b356a6a9058e98f9c92054afd952b91cb127702c3a78a3372dca202e0d4

Observation 76b04fa7-f219-457d-8a95-8501cda66db9 · outbound

This paper cites Spherical perceptron as a storage memory with limited errors.

Deep ReLU networks -- injectivity capacity upper bounds Spherical perceptron as a storage memory with limited errors

Reference 70

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local_arxiv, observed 2026-08-11T00:14:23.383232Z

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.

source=pdf_text observed=2026-08-11T00:14:23.088401Z digest=sha256:84cfd0eb0bb621daf825c14340e7095a3be9c7eaefaf6b2156ff92e161505062

Observation fcecc65b-acc5-4245-a1d9-177734881da0 · outbound

This paper cites Fully bilinear generic and lifted random processes comparisons.

Deep ReLU networks -- injectivity capacity upper bounds Fully bilinear generic and lifted random processes comparisons

Reference 71

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T00:14:23.092225Z digest=sha256:7197b360b95d8170d915222ec02fa9de20a6b426fc8b358ea3a9e00b409b8e26

Observation 7c556cde-b880-41a5-a0fc-e87e01c7ae12 · outbound

This paper cites Generic and lifted probabilistic comparisons -- max replaces minmax.

Deep ReLU networks -- injectivity capacity upper bounds Generic and lifted probabilistic comparisons -- max replaces minmax

Reference 72

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T00:14:23.096050Z digest=sha256:9a30f066bdb1381d2c40db4a3298ff65db0aee45fd9e22dcacf7f25252271a45

Observation ba80d0fb-e0b4-4136-8228-999f1b2be320 · outbound

This paper cites Bilinearly indexed random processes -- \emph{stationarization} of fully lifted interpolation.

Deep ReLU networks -- injectivity capacity upper bounds Bilinearly indexed random processes -- \emph{stationarization} of fully lifted interpolation

Reference 73

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.100381Z digest=sha256:06ebecab93624e132e50baa5402fafc5c02b9b1c9d1de0379cae4bb5f00c543b

Observation 6c2207c8-6af6-47ae-a1bc-1f75cb9b289a · outbound

This paper cites Binary perceptrons capacity via fully lifted random duality theory.

Deep ReLU networks -- injectivity capacity upper bounds Binary perceptrons capacity via fully lifted random duality theory

Reference 74

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.104558Z digest=sha256:2377c5766e10fd9fd0fb50f6d435674c7205d21f14b5138b98aa874de2eb16ba

Observation cb6fc16e-de48-4c41-baad-aedee293e2c1 · outbound

This paper cites Capacity of the treelike sign perceptrons neural networks with one hidden layer -- RDT based upper bounds.

Deep ReLU networks -- injectivity capacity upper bounds Capacity of the treelike sign perceptrons neural networks with one hidden layer -- RDT based upper bounds

Reference 75

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local_arxiv, observed 2026-08-11T00:14:23.305071Z

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.

source=pdf_text observed=2026-08-11T00:14:23.108993Z digest=sha256:78a52316f3e2939efeea994a2ded839f3fa43e9d9fa0ad80b33fd252c100905e

Observation 3eeb2456-cd2c-48a6-b52d-382a3de4075c · outbound

This paper cites Fl RDT based ultimate lowering of the negative spherical perceptron capacity.

Deep ReLU networks -- injectivity capacity upper bounds Fl RDT based ultimate lowering of the negative spherical perceptron capacity

Reference 76

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.113282Z digest=sha256:bc3eb9f0f537d3e525a202609d5a8ba251ea5334507c1789782e567623554cbf

Observation 1ca4c658-effd-46bd-9e20-47a074515e07 · outbound

This paper cites Fully lifted interpolating comparisons of bilinearly indexed random processes.

Deep ReLU networks -- injectivity capacity upper bounds Fully lifted interpolating comparisons of bilinearly indexed random processes

Reference 77

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.117187Z digest=sha256:3de4eabf57406b90ee22f49fe073c0f04655e5aa9b78054294663fd52688f0b4

Observation 97720d8e-45c7-4a1d-b722-f505694a870b · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 78

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.121319Z digest=sha256:3c7e7c7ed426ce2742591fdab99208212c54cb5e7dc28e70b7ca2cd90fbfcad5

Observation 1e263452-5765-402a-9850-0cfea534e43a · outbound

This paper cites \emph{Lifted} RDT based capacity analysis of the 1-hidden layer treelike \emph{sign} perceptrons neural networks.

Deep ReLU networks -- injectivity capacity upper bounds \emph{Lifted} RDT based capacity analysis of the 1-hidden layer treelike \emph{sign} perceptrons neural networks

Reference 79

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 871fd412-fd84-458a-b62c-3150253eaa47 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 80

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raw_fallback, observed 2026-08-11T00:14:23.716829Z

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.

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Observation 13d75a76-1b92-407c-b4b5-21aa8eba4455 · outbound

This paper cites Fixed width treelike neural networks capacity analysis -- generic activations.

Deep ReLU networks -- injectivity capacity upper bounds Fixed width treelike neural networks capacity analysis -- generic activations

Reference 81

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verified exact
local_arxiv, observed 2026-08-11T00:14:23.221139Z

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.

source=pdf_text observed=2026-08-11T00:14:23.138004Z digest=sha256:a58683f53a49baa78ea2bc75e4823e1dcf30c530dcd9538533faa9bea3a08c27

Observation 6aac608c-7fce-4455-81b0-16ec9288806a · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 82

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 15176c29-a009-4883-b4d6-10fb15bbd0f1 · outbound

This paper cites Talagrand.

Deep ReLU networks -- injectivity capacity upper bounds Talagrand

Reference 83

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no resolver link, observed 2026-08-11T00:14:23.146567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.146567Z digest=sha256:82931a66a2a6af8f70520f6f41b7cef8225b85290c65ad9253041bca57177100

Observation 020eb0a4-72a8-4556-8083-a78d99b04f56 · outbound

This paper cites Talagrand.

Deep ReLU networks -- injectivity capacity upper bounds Talagrand

Reference 84

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no resolver link, observed 2026-08-11T00:14:23.150445Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T00:14:23.150445Z digest=sha256:b725c8bfdf54150f1a755f224d0decaa90ff3a9ab7224aeab731403d0234b0b3

Observation 58a7d077-487e-4bef-bea8-6525752ccd34 · outbound

This paper cites Venkatesh.

Deep ReLU networks -- injectivity capacity upper bounds Venkatesh

Reference 85

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verified fuzzy
raw_fallback, observed 2026-08-11T00:14:23.672392Z

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.

source=pdf_text observed=2026-08-11T00:14:23.154588Z digest=sha256:004cab81a247f254ecb80c3a3dfdf40766db8b2d38e59bfb8b2ba42f9959095a

Observation 4964d67a-dab7-4b60-8500-010ecd67be42 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 86

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unresolved
no resolver link, observed 2026-08-11T00:14:23.159219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.159219Z digest=sha256:bcf5eca3bc1aaabb67ad0667bdffa694e65cac0f245e00421aebeb3c6205ec58

Observation 2b63a589-d62b-4d62-bdff-0af57758462f · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-11T00:14:23.163736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:14:23.163736Z digest=sha256:c7496df436cb602468998d0910a014c14d5eb0d15e653e7541e520a78974ccb3

Observation b7cd6013-4acf-4c31-8607-9dcd5b307e3d · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 88

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:14:23.641351Z

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.

source=pdf_text observed=2026-08-11T00:14:23.168473Z digest=sha256:bf7eeeacc63f461ff13cc7731a1cf66a944118397d6a78bbfe6ab7da8a3f4d74

Observation 7a7574da-dcd7-4e2f-bd0f-e571dbb43481 · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 89

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:14:23.628939Z

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.

source=pdf_text observed=2026-08-11T00:14:23.172523Z digest=sha256:594b259bdee79853303b955f42b7e07d2f260971fc2eeb56fc64a48ad38b63ec

Observation e8aafc14-e96a-4650-b247-e226229df38b · outbound

This paper cites an unresolved cited work.

Deep ReLU networks -- injectivity capacity upper bounds Unresolved cited work

Reference 90

Resolution
unresolved
raw_fallback, observed 2026-08-11T00:14:23.616439Z

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.

source=pdf_text observed=2026-08-11T00:14:23.176737Z digest=sha256:42a6edcf350c7727c66b2d6930784e27997765ea914cd843f0c08d020395828e

Observation db152ac8-277d-4418-8bee-d50af53e9dc3 · outbound

This paper cites Exact capacity of the \emph{wide} hidden layer treelike neural networks with generic activations.

Deep ReLU networks -- injectivity capacity upper bounds Exact capacity of the \emph{wide} hidden layer treelike neural networks with generic activations

Reference 2024

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:14:23.241493Z

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.

source=pdf_text observed=2026-08-11T00:14:23.133190Z digest=sha256:c898978f2d998081bf253e25adc3262d0c13e314afcc6d633b9910c5f4feb738

Pith citing papers

Observation 8c03c6bd-8b6c-4482-b46c-088ac55146d8 · inbound

Optimal spectral initializers impact on phase retrieval phase transitions -- an RDT view cites this paper.

Optimal spectral initializers impact on phase retrieval phase transitions -- an RDT view Deep ReLU networks -- injectivity capacity upper bounds

Reference 102

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no resolver link, observed 2026-08-06T23:29:20.785752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:29:20.785752Z digest=sha256:43ca6c23817fbb14b681ce24c5f64d11dde71f2cc04f6e2f414758be90fe01ba