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Paper Citation Record · LEDGER

Continuous-in-Depth Neural Networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2008.02389.

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

pith.paper-citation-record.v1
2008.02389 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:08:40.763528Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T14:44:36.893478Z

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 11bf29ab-e280-4bb1-b7e8-308966b47756 · inbound

Denoising Diffusion Implicit Models cites this paper.

Denoising Diffusion Implicit Models Continuous-in-Depth Neural Networks

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-24T14:44:36.896613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-24T14:41:23.935708Z digest=sha256:03e854ad377595502463fa82eb9ec3b0d3ab420f16ec5291b314dfe18fce18a1

Observation b0c105c2-8a0f-4628-96c7-1c6d29ac736a · inbound

From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics cites this paper.

From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics Continuous-in-Depth Neural Networks

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-08T10:08:40.763528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:08:40.763528Z digest=sha256:7d77001406d6ed5c03e6ef131a16918c335c3886f197dab04b1fc9ac7a83ff17

Observation cadca0ba-2874-49f9-b929-5968d4d225e6 · inbound

Recursive Bound-Constrained AdaGrad with Applications to Multilevel and Domain Decomposition Minimization cites this paper.

Recursive Bound-Constrained AdaGrad with Applications to Multilevel and Domain Decomposition Minimization Continuous-in-Depth Neural Networks

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-06T17:14:32.559832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:14:32.559832Z digest=sha256:c18ce29581967b57f20d1a755f526868094ef8f0da4dd19dabdd3df10f971ee5

Observation 0573d5d3-bf7b-4322-af62-52d0e3654de5 · inbound

Deep Learning with Self-Attention and Enhanced Preprocessing for Precise Diagnosis of Acute Lymphoblastic Leukemia from Bone Marrow Smears in Hemato-Oncology cites this paper.

Deep Learning with Self-Attention and Enhanced Preprocessing for Precise Diagnosis of Acute Lymphoblastic Leukemia from Bone Marrow Smears in Hemato-Oncology Continuous-in-Depth Neural Networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T17:01:41.051207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:01:41.051207Z digest=sha256:e926feb2d2e5e360ae65978cfceb8242e96fc64644b74c6dced3a90c46e7a4e4

Observation 76240b0e-1c7a-4a5e-8463-466e8db71276 · inbound

TRASE-NODEs: Trajectory Sensitivity-aware Neural Ordinary Differential Equations for Efficient Dynamic Modeling cites this paper.

TRASE-NODEs: Trajectory Sensitivity-aware Neural Ordinary Differential Equations for Efficient Dynamic Modeling Continuous-in-Depth Neural Networks

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T05:10:54.395932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T05:07:45.633258Z digest=sha256:c6d44d1fee9d2f4ff58f22ba7d495c57e5b62588a430d7e040bfb62172315fb0

Observation f00116c2-2e7e-4db9-a5ea-4ffb3dd2a107 · inbound

Continuity Laws for Sequential Models cites this paper.

Continuity Laws for Sequential Models Continuous-in-Depth Neural Networks

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T07:56:26.768809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-12T01:32:13.445719Z digest=sha256:7d7439cc347188bd9a2b0f05c25d747d5f0ddfc2cd2241921ed601494d982c89

Observation 909e903f-3c57-4453-9ed4-c0b82372598b · inbound

A manifold-aware Neural ODE surrogate model for stochastic induction heating with anisotropic electrical conductivity cites this paper.

A manifold-aware Neural ODE surrogate model for stochastic induction heating with anisotropic electrical conductivity Continuous-in-Depth Neural Networks

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-04T17:56:57.453270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:56:57.453270Z digest=sha256:5f6153c498e6fa63723cb2da7b591dc47db048d6e2e67b3a0352aa6a31bbd676