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Paper Citation Record · LEDGER

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View

As of 16 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 0 inbound Pith citation observations for arXiv:2608.01357.

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

pith.paper-citation-record.v1
2608.01357 v1

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:14:01.621776Z

measured 83 of 83 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

83 of 83 outbound references displayed

  • verified exact3
  • verified fuzzy31
  • unresolved49
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 49f2c36c-921d-4302-863f-764703f74f2b · outbound

This paper cites Abramowitz and I.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Abramowitz and I

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.327022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fb493bb1-99fa-4634-ae96-c539f15f56cd · outbound

This paper cites Arcang´ eli, M.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Arcang´ eli, M

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.331877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.331877Z digest=sha256:4afffe628d393d7d69006b983ac4fc2ad1a96e870d05c745df6cc8fd5bf26d2f

Observation dc80e775-9edb-482f-837a-07f2aaedb4de · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.335344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.335344Z digest=sha256:44bf98a5a6dd7de6baf39ba6dc776ad15d18c661a179b5c59e812cd56a0496c8

Observation eb612364-5c56-4cd6-b7af-a30efbe646ad · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.600939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 432e34ec-3e82-42f5-aa55-808ceb826411 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.591124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.342578Z digest=sha256:c2c933f1c91dc25d45b1892b94de72a29063d9a25b8fc16116074250b750470b

Observation b304a560-0541-49d1-9630-05cbce741c06 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.580409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.346051Z digest=sha256:bd81f6a5fb11ea18c676e04f2c71867b7406bdef9933f4c9894dd49e065a8587

Observation 78e63a44-d7ef-4bbb-b760-a2763ff17231 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.567753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.350181Z digest=sha256:814c21343d45d85bb1cec6331cc20f06a7987956610e2ce5777cf84c5a93fb22

Observation 0f4d581e-588f-4259-9b4b-157d2978c66e · outbound

This paper cites Bathe,Finite Element Procedures, Klaus-Jurgen Bathe, 2006.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Bathe,Finite Element Procedures, Klaus-Jurgen Bathe, 2006

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.557389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.353838Z digest=sha256:b031a0625702bf4ac02b60a364fd52f81acbe6ac7ddcddd34fc5951154122407

Observation 91bffc4f-8e36-45e4-b17f-0fcf0f823a55 · outbound

This paper cites Bengio, Learning deep architectures for AI,Foundations and Trends in Machine Learning, 2(1) (2009), 1–127.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Bengio, Learning deep architectures for AI,Foundations and Trends in Machine Learning, 2(1) (2009), 1–127

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.546214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.357953Z digest=sha256:cb34a9bea30c8037e5feafee10a64fec100fa8b00111b67bad17e5f26724ef8b

Observation 0874f619-755f-4bb2-ab29-7ef1529c27ef · outbound

This paper cites Bertoluzza, R.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Bertoluzza, R

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.529703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.361399Z digest=sha256:77af519a950246ec04dcb308c8b5d83046439155b0c7a2c33a34b76ab93d5a8d

Observation 9eb64b52-bada-473a-a32e-5f3ce5fce74c · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.517028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.365258Z digest=sha256:91a011d048df5c313eab1e662f9f01dbe552120e730e99333c20eb7d12f9ef2f

Observation a3beac65-126c-47e4-8122-7671095365f0 · outbound

This paper cites Bungartz and M.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Bungartz and M

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.506858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.368861Z digest=sha256:74625a1d29b913a7215f778f0e2fee66bfc5315d87dab302e7c1f41dc135a265

Observation 9d992c1b-6f3c-4aba-a953-f2ee9ee09002 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.495938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.372564Z digest=sha256:f3aa803c9e682229d4bbf22e2021e0006821c5b6f2a34fc25c204d38a6c59d6a

Observation e31af6f5-495d-4250-bae6-cb834578c840 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.485238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.376065Z digest=sha256:cea69294863e8c99456c5f1253689d3577b4d67ddb75467f5a0a0e6dbabd3945

Observation 3da51618-5032-4bdc-b2ef-f07c6c534667 · outbound

This paper cites Cucker and S.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Cucker and S

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.474657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.379879Z digest=sha256:af87bb99c40ec76c9f7bb482981b229fca1cad614f5213e379107088d32a4256

Observation ce6f78d4-c713-4027-aeaa-af8ab35c5b18 · outbound

This paper cites Cucker and D.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Cucker and D

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.464170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.382736Z digest=sha256:16e4dea095fcbcb7dafedc3144446854669e1075cbae949ff6ece22bca8f8d43

Observation 67b7d4be-7d48-494c-82c1-324a9f40834e · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.453369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.385868Z digest=sha256:ff2a02da24214dbf38ffa950c91c5c1c649846eef21277bf40746a5c5e865e28

Observation 65b25045-49e6-4a45-b957-a79666121f1c · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.441610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.388786Z digest=sha256:e6ded9b7536a163e76b92e0a1ff37e12284356b93ed07db06a20969563a98f28

Observation 18e50840-26cd-452c-8c31-258a9bb178dd · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.429060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.391923Z digest=sha256:1633e79a27b2626336ef7210ed7090b8be4eb7ae6f01b20191e0c1291fa7b307

Observation 234a1ce5-83b2-4fcc-aa50-be09e6108b75 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.415434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.394599Z digest=sha256:8cc74dfc4531f999cdff6b97d0f0a7a32f5c1fd7af97d4dc9ceabe85a33bf17e

Observation 35cd0f17-ca8b-455d-a4b7-fbdd807d206e · outbound

This paper cites Eldan and O.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Eldan and O

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.401856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.397632Z digest=sha256:ca7314a0b7d4251e7f9a6fb0ddb55f1385f90fdd71d732eed9bb4de884c16fb0

Observation e4c352a5-4884-4ea2-99af-e2fb24fce5fa · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.386958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.400364Z digest=sha256:942e6f2cfbc06b5041f8d84319629784a23ad07fea1bc77a0141250f9d5fe32a

Observation 921b60e6-fe0b-4edb-a736-8314e805592a · outbound

This paper cites Harvey, C.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Harvey, C

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.374772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.402919Z digest=sha256:bb0840f2916996b971d9ee6e33512a0647de0e7e16ccd32763a34b920ec9b1b1

Observation 72503e03-0bc8-4b26-aee1-15273f14d9a6 · outbound

This paper cites Expressivity and Approximation Properties of Deep Neural Networks with ReLU$^k$ Activation.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Expressivity and Approximation Properties of Deep Neural Networks with ReLU$^k$ Activation

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.405600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.405600Z digest=sha256:39df83da5f75b4161b76b3740a7c1e4260651229f95c39487dabdae348c0d613

Observation 7b299876-25f1-4f9a-a880-05546e1fd5f5 · outbound

This paper cites Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on H\"older Class.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on H\"older Class

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-15T15:14:01.808289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.410186Z digest=sha256:9b7e256120980ecf8c76d59f76cc5d91672c7df3b937a922754f7a0b4b255acd

Observation fdbcd207-6981-46ef-bece-9e25c408f69b · outbound

This paper cites Jin,The Finite Element Method in Electromagnetics, John Wiley & Sons, 2015.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Jin,The Finite Element Method in Electromagnetics, John Wiley & Sons, 2015

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.363995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.414352Z digest=sha256:3ac4a554f94858d1c2ac93b8f8690d5e1a9aab29ee0033d48b851d3c84064c23

Observation 37f440d2-64b3-4c77-8ec3-092a3058ced3 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.350063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.418074Z digest=sha256:fda1ee26300c94b5087dbbde3566b166199b7822f7cda7db19f92fcf6dc54568

Observation 51612a28-29df-44af-bfa8-726b88223c6e · outbound

This paper cites General superconvergence for kernel-based approximation.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View General superconvergence for kernel-based approximation

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.421626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.421626Z digest=sha256:6d5d4ab259603c1eaab5c580e38b9089ba6571c8064b490f36dfe7a512fad764

Observation 547dbcdb-8f37-4772-a293-db9dcdb98c1a · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.337818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.425543Z digest=sha256:90413d65cc2685c03dadae4765c9aa88407ab974f3273c68d453010e7728f9d4

Observation f91daaa0-0efe-4715-87cf-f6309431f1f5 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.327705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.428828Z digest=sha256:dc54d9cb83338e167d5c06ed3e5b6932f88f6396c15fa9639cb3de89435a5da1

Observation 0d1650f8-3bea-41de-92ee-33d426c8c839 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.317285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.432663Z digest=sha256:8568a22d2b49fedc823d9715ec46a84c6f31808db8ded301eca6226e64139fc0

Observation de464df2-eab5-4828-9c53-b2e57da3bee0 · outbound

This paper cites Koltchinskii, Rademacher penalties and structural risk minimization,IEEE Transactions on Information Theory,47(5) (2001), 1902–1914.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Koltchinskii, Rademacher penalties and structural risk minimization,IEEE Transactions on Information Theory,47(5) (2001), 1902–1914

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.307341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.435965Z digest=sha256:21efc23d6c87f069f3a86a180df56513533513fd683984d568c21b6ed75bf67d

Observation 85e85b82-c6ee-4f9c-960a-b38f408a5f26 · outbound

This paper cites K˚ urkov´ a and M.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View K˚ urkov´ a and M

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.296827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.439276Z digest=sha256:99232839abf079dff632541979a8fe0fe6547612ac4462beeaf6a47b1ea4cf5d

Observation 8581f05a-47a3-4315-9c6c-3b43e1373c38 · outbound

This paper cites K˚ urkov´ a and M.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View K˚ urkov´ a and M

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.285690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.442471Z digest=sha256:22a7454da286ebb137ebe9b43b6ffdd4a6f5a8548366869c99838e6bbeb522ad

Observation 2c9c5dcb-cdd3-4d11-924e-043e9d948451 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.274756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.446428Z digest=sha256:3825d52471636c35a82e23fba9ebbf8047431594dad0e49ee319a6154420943b

Observation 6a544930-f0a1-4d68-9b13-588da45883c4 · outbound

This paper cites Lewicki and G.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Lewicki and G

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.264547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.449820Z digest=sha256:9233a3c13b1ad485b9d4971249c3dd76b9a495705337d47cf3e667015498211b

Observation f2e488af-be4d-4bf4-8feb-f3cc76c65946 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.253574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.453306Z digest=sha256:1b3463a5475928a5377abfcc44543c96f1ded320b545dc479a32a0ae3a14db84

Observation c5ea7eb1-6caf-400b-bef6-48cb52c7f067 · outbound

This paper cites Integral Representations of Sobolev Spaces via ReLU$^k$ Activation Function and Optimal Error Estimates for Linearized Networks.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Integral Representations of Sobolev Spaces via ReLU$^k$ Activation Function and Optimal Error Estimates for Linearized Networks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.456811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.456811Z digest=sha256:cf7dfc8aa498c0f76366f3298c45e96508d4abb9314bac9ab038250c6b262998

Observation 00d8785d-b656-4506-ad9d-afdcc1454de9 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.243401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.460474Z digest=sha256:938c091168c9c26c12e658060a8578fac46c048851331e8493f155e13f9edb67

Observation a63f6124-7376-4db0-8c77-67da60dca8f2 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.233101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.463821Z digest=sha256:8fca4ba21efa3f463700485177c00adca505c7f37bfc091e5eb359633ec504e3

Observation 13da4122-bad2-43d6-ad42-1398cb662d67 · outbound

This paper cites Maiorov and A.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Maiorov and A

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.222715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.467227Z digest=sha256:a168b83db3c2e00c37fc5cfab7a9b6ba41308ec0dcda5d9afcaf7a564e8a33d3

Observation 05eb8b09-0272-4be6-ae16-ae7feb9511ce · outbound

This paper cites Mao and D.-X.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Mao and D.-X

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.212358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.470651Z digest=sha256:1311df82a13b6be8e3ef93e7359365dcfe31eed4add03d3ac64b94305ed23d3f

Observation 16399f6a-1d92-4278-8d22-ee22e6a7279e · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.200428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.474274Z digest=sha256:2078ee4f7cdcdcce7d706e0801f951343b2d0674f680abccdecf5ab6351835ad

Observation 82f6f3f7-6e4a-4be2-ba5a-a089481a7afc · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.187982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.477876Z digest=sha256:5cc4f418936d4d51cf73ca3fee265cb00b2b03928e1cec010b09bccc8146ac91

Observation 42fc2396-7249-427c-87a4-60d7591c6d33 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.174671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.481565Z digest=sha256:2d793242b56b38d5682417f18d63d646dd6c9a00a39f618529230e3516e02207

Observation 06f0a1c5-27ba-45e4-b8c9-56a936b47b5b · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.164203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.484956Z digest=sha256:3ca77d9438965243a3908537cbacc5fe68ba77d2725e733c293ff6ab9c09591f

Observation a72357db-239b-4ba1-b901-35dfc3f8dce4 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.154848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.488589Z digest=sha256:271b93f8cad1f6b0baf8e6f1ffa56beefb61c412c602065f23654c8b187dcd18

Observation ea4f9546-0d03-4954-ae39-7ae5eca6ab08 · outbound

This paper cites Moaveni,Finite Element Analysis: Theory and Application with ANSYS, 3rd ed., Pearson Education India, 2011.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Moaveni,Finite Element Analysis: Theory and Application with ANSYS, 3rd ed., Pearson Education India, 2011

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.144222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.491438Z digest=sha256:f1efa8b18f0535405069d56bc23aba3ef93b04208b26bd2e20ccf58f718635bd

Observation a197e54b-9d20-4d89-aaee-8df31303aff5 · outbound

This paper cites Mohri, A.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Mohri, A

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.132792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.494303Z digest=sha256:da5d9350529bde37b99d57f7a2e896fd24b658cf6cb420a3d79ea25b895d832f

Observation eee8f72d-534a-4b02-80c1-59f045b4d76a · outbound

This paper cites Montanelli and Q.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Montanelli and Q

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.121147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.497157Z digest=sha256:188029785bde8c79625538cc06b1292a1cc552af8ab9499be928755e10a8c300

Observation 02c87742-193b-42b7-a14a-5d608378e388 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.110429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.500108Z digest=sha256:85a6ab867a7cacf6b61326d7da1b6a7626a2a1d81f8737059d62c0f014e0fb03

Observation 16b351e9-0a1b-4405-b086-59c3d1a9be4f · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.099318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.502973Z digest=sha256:a8fa63a132b2e0a57441c0df52521152fe68da29575407ceb3d9769b9f2cbce4

Observation c9664bbe-efdf-4a97-b066-bee16e70ea7c · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.086296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.505669Z digest=sha256:4e883c7d387f09b2fe66bc9d976caed67d484123bdb7a6ad47aed3e4e509a4f1

Observation bd3f6054-3f59-4db4-816d-14613233b707 · outbound

This paper cites Poggio, H.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Poggio, H

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.074599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.508724Z digest=sha256:a65d60b2ca818dca57fdd3e7a7f7bdcbbf1381caf752a63866ad187575e5afc1

Observation 786aab64-a9c4-4c4d-be33-f2b2a721463d · outbound

This paper cites Reddy,An Introduction to the Finite Element Method, 1993.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Reddy,An Introduction to the Finite Element Method, 1993

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.061748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.511471Z digest=sha256:4ea3e1cac3a1887b745d6cbe5717b5ad8d83ad58821b8b0c650e7c5438a6cf53

Observation 9147bb7a-d091-43cc-9b50-68e14bd2a1a3 · outbound

This paper cites Schaback, Improved error bounds for scattered data interpolation by radial basis functions, Mathematics of Computation,68(225) (1999), 201–216.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Schaback, Improved error bounds for scattered data interpolation by radial basis functions, Mathematics of Computation,68(225) (1999), 201–216

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.049887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.514117Z digest=sha256:0318883ca08dce93d8130aff4d6abade1f4cb2bf870320c9a8f3a57077091b54

Observation dbd8a644-8458-4b24-9230-98adc22a022c · outbound

This paper cites Schaback, Superconvergence of kernel-based interpolation,Journal of Approximation The- ory,235(2018), 1–19.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Schaback, Superconvergence of kernel-based interpolation,Journal of Approximation The- ory,235(2018), 1–19

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:02.038494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.517369Z digest=sha256:3a81473b1436032cb845c022e684d8aba0087c25f5b44be8634a67a2cb0f3b24

Observation c40e4fe8-6a1e-403d-8588-1f29fecff3c7 · outbound

This paper cites Deep Network Approximation Characterized by Number of Neurons.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Deep Network Approximation Characterized by Number of Neurons

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.521184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.521184Z digest=sha256:7644859cf6fb863bd2b09fa33883dfa2c11ca42138a930c333f1bb9cabdf2923

Observation 0b18ff21-6aae-4ec0-a39a-8f6a5111676d · outbound

This paper cites Deep Network with Approximation Error Being Reciprocal of Width to Power of Square Root of Depth.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Deep Network with Approximation Error Being Reciprocal of Width to Power of Square Root of Depth

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-08-15T15:14:01.759042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.526964Z digest=sha256:75ce9cf42f9fd8f339bdc7f7c17070b42d7575c5d85ec5c7a8db627fd284d9b5

Observation 033542be-cc05-449c-b0f9-80f05991f87f · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.026196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.531155Z digest=sha256:cb877548b4add6997e9e6a5f6dac53a39b0e067e80ef22a8f92222d4111fdd5a

Observation 6ba1842e-135b-4bea-801e-429a564f9830 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.011717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.535112Z digest=sha256:f9b418cef6733be24ddcb01da93d280d826384d2aa06702ba499dcd4be3c16e3

Observation 868c4cd2-1a19-472d-8349-5892e2e5831c · outbound

This paper cites Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.538697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.538697Z digest=sha256:6c3302f994d311f20248ad9fb5780c5f552d7baa6f1f6270c728b5c639fb329b

Observation 433e8fb9-3496-4615-8384-1dcac5add4be · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 63

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:02.000786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.542227Z digest=sha256:8a817ada154f857ea73811917bcb0b44f4be19d0728fa8f802c9be7f7c3c44f0

Observation b3ba7bb7-7b1a-4429-a777-9a3ab9760348 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 64

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:01.991122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.545620Z digest=sha256:ab03cdb9514b3e8aa30e5a3b5bcc2c90bdcec4cc481c8feaadeeb952daa6b1cf

Observation 9dbc038d-8331-4cbf-81ef-4ed70a3f6697 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 65

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:01.980398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.549441Z digest=sha256:b431b8dab8f53d997f3b10929c0e2055377de121b4f2155cc5751ff79bac8458

Observation a6b53c54-5c5d-4990-922e-6fc5109ac1bb · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 66

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:01.969879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.554753Z digest=sha256:3da84757c9205eb9a22027c8a1ddaa9e71c9c12bd1db54d0c3c0108e17364ea6

Observation eed532c4-4cce-4492-b9eb-d16dca4cfbe5 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 67

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:01.960004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.558634Z digest=sha256:8bb941aea3133008db6c36acda596eb04f92fd9f876ed647a04332c4e275a6d6

Observation d070e93b-1a89-4f1e-947c-343ea6596f07 · outbound

This paper cites Sloan and V.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Sloan and V

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.950719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.562477Z digest=sha256:2522bf7f37c8ca86bfa6be1615926e090d33a4f962740c9c99f75b98cfa1c38b

Observation 64176712-47d3-4c94-aa9f-79f74de6bcbb · outbound

This paper cites Stoer, R.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Stoer, R

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.941788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.566112Z digest=sha256:9ede30d176768eedaf0d25a374568a33d1da3b0dd1f981b0b8ca1d51cfc23f46

Observation 69470c44-e779-4bc7-8002-fad89e432eed · outbound

This paper cites S¨ uli and D.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View S¨ uli and D

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.931773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.570257Z digest=sha256:1548c13672ff84327f9eb8dd48ccbdfb6f003e84f2beec406b672ccdd8019399

Observation 16d6c833-80f4-4b5a-b64d-abbb2205bc10 · outbound

This paper cites Szeg˝ o,Orthogonal Polynomials, vol.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Szeg˝ o,Orthogonal Polynomials, vol

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.921365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.578433Z digest=sha256:1f3a2d0b103feaefb50034c725caafac3a3837d4ed82bb3442f462ce1ce2e433

Observation 52f7024a-59de-43c4-bd32-31a1e449f7a6 · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 72

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:01.911241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.582168Z digest=sha256:c1098a7256eef405b517a7a8d19ccf29059c2c0a11a3845c44b74f21ce454827

Observation 09ce994f-eafe-4bc0-8ace-bb0fe34d056d · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 73

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:01.896650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e53e5cdb-e873-41b2-87ab-af6f149afd8d · outbound

This paper cites an unresolved cited work.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Unresolved cited work

Reference 74

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:14:01.885807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.590084Z digest=sha256:583c39a774dd95a0d0bb82fbc9e1a74d8cf7676a150ee3b3b6786ddbebbf40ca

Observation cb8a23c0-b1e3-4926-becb-7739e5edb229 · outbound

This paper cites Wendland and C.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Wendland and C

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.873074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.593723Z digest=sha256:3b3be5ab042fae550f98d5e491bc3b8bc0bc2d32ac66293f413862375e01df71

Observation 67b72d8d-ac71-493a-b846-b68f6d4868d7 · outbound

This paper cites Wenzel, Sharp inverse statements for kernel approximation: superconvergence and satura- tion,arXiv preprint arXiv:2601.01808, 2026.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Wenzel, Sharp inverse statements for kernel approximation: superconvergence and satura- tion,arXiv preprint arXiv:2601.01808, 2026

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.597147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.597147Z digest=sha256:51bb3592516b7a5a42e4438ab9fe92f1e96bb6dc908868d227834aa4a2b21fb8

Observation 162c109b-eb1f-437e-a571-6714d94373ee · outbound

This paper cites Xu, Iterative methods by space decomposition and subspace correction,SIAM Review,34(4) (1992), 581–613.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Xu, Iterative methods by space decomposition and subspace correction,SIAM Review,34(4) (1992), 581–613

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.862737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.600457Z digest=sha256:094f0cd905f6102e3b9cbd4ccfc667b6f241c49b259a88be8961ab0b393d083c

Observation 34ac7f0c-acf1-4871-ac39-e4d3abd7e083 · outbound

This paper cites The Finite Neuron Method and Convergence Analysis.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View The Finite Neuron Method and Convergence Analysis

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.604888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.604888Z digest=sha256:bc96a3085af97a2fa8ff629a3112ddeeefee2f4b40a32e75e595aa1b7027e54e

Observation 35b66c45-bdae-49cc-9930-920cc05a868b · outbound

This paper cites Nearly Optimal Approximation Rates for Deep Super ReLU Networks on Sobolev Spaces.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Nearly Optimal Approximation Rates for Deep Super ReLU Networks on Sobolev Spaces

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-15T15:14:01.608610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:14:01.608610Z digest=sha256:f161607d4b53819f6cd066f2399b73516e704a61b658dd226a5c9766990325ce

Observation d3c705b8-5ec8-4e97-a307-cb4816e33f0b · outbound

This paper cites Optimal rates of approximation by shallow ReLU$^k$ neural networks and applications to nonparametric regression.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Optimal rates of approximation by shallow ReLU$^k$ neural networks and applications to nonparametric regression

Reference 80

Resolution
verified exact
local_arxiv, observed 2026-08-15T15:14:01.659841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.611692Z digest=sha256:3cd3ab7a731a9d222ce9f837619643fb5b44c07a6ee88ea9072e8c2a2831112e

Observation 0628b4a4-f128-430c-bc83-a9f9be61e083 · outbound

This paper cites Yarotsky, Optimal approximation of continuous functions by very deep ReLU networks, in Conference on Learning Theory, PMLR, 2018, 639–649.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Yarotsky, Optimal approximation of continuous functions by very deep ReLU networks, in Conference on Learning Theory, PMLR, 2018, 639–649

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.851936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.615059Z digest=sha256:74400964b7cbd8b333857b318a537771c6038243ede4b4c57cb5ce41905db759

Observation 4bca685f-1aef-402f-9f13-221c48ac3213 · outbound

This paper cites Yarotsky and A.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Yarotsky and A

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.841342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.618291Z digest=sha256:779fcf0c0fd251e4313768e1a3e766adfa0d54506193cb3d604f3a8ebb98edb8

Observation ea5dc48c-a3df-4e42-9ca4-d506ff7f92f1 · outbound

This paper cites Zhang, Z.

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View Zhang, Z

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:14:01.830371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T15:14:01.621776Z digest=sha256:e8ddee7a166cd5c74f65c39f65072ce1140e4e322f2e4e71544f485fd1c0e469

Pith citing papers

No inbound Pith citation observations are available.