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Paper Citation Record · LEDGER

Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2009.10683.

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

pith.paper-citation-record.v1
2009.10683 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:34:06.490749Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T08:39:12.062601Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 260cba31-159f-4c93-a722-7b2ac7e1b932 · inbound

On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains cites this paper.

On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-24T08:39:12.065712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-24T08:38:59.401534Z digest=sha256:62700237f1064946237ce742d8f76e5315741a4573059d9d580abe9ab55ed734

Observation f7c0d8fd-bcbc-476a-b6ff-98f99a298067 · inbound

Optimal Convergence Rates for Neural Operators cites this paper.

Optimal Convergence Rates for Neural Operators Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T05:34:06.490749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:34:06.490749Z digest=sha256:85dc41166e04e0eb541c2128803c206e6317b08b8fb194c132ece4a6a9c073b2

Observation ed07b979-db5d-4582-b33b-c260fffe33ea · inbound

Deep Ritz method with Fourier feature mapping: A deep learning approach for solving variational models of microstructure cites this paper.

Deep Ritz method with Fourier feature mapping: A deep learning approach for solving variational models of microstructure Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-08T19:29:47.852242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:29:47.852242Z digest=sha256:64324b73bd0f0a2f5950b4b6c29db95641733342f61cd345399d0b833c2448e2

Observation b901b355-5e5a-4e77-99be-5dacd2d370aa · inbound

The Cost of Discretization in Functional Linear Regression: Minimax Rates and Adaptation cites this paper.

The Cost of Discretization in Functional Linear Regression: Minimax Rates and Adaptation Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-13T03:41:36.654380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T03:41:36.654380Z digest=sha256:50c8d39ab92751386994379a146156fd23ee09e8dd8489611545c99ed75df23d