Paper Citation Record · LEDGER

An optimal control approach for neural network architecture adaptation with a posteriori error estimation

As of 10 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2607.07637.

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

pith.paper-citation-record.v1
2607.07637 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T04:31:29.598247Z

measured 27 of 27 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 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

27 of 27 outbound references displayed

verified exact7
verified fuzzy19
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 83994ffe-4a39-49c9-a4ff-3698aedda407 · outbound

This paper cites Learning multiple layers of representation.Trends in cognitive sciences, 11(10):428–434, 2007.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Learning multiple layers of representation.Trends in cognitive sciences, 11(10):428–434, 2007

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.913800Z

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.

Observation 13c43772-aab0-479d-b988-3039fcb7d16f · outbound

This paper cites Visualizing and understanding convolutional networks.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Visualizing and understanding convolutional networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.907427Z

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.

Observation b18a8450-8f19-4488-b470-fab3236779d5 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-07-09T04:35:57.551800Z

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.

Observation 5b5062b5-ac0d-42f4-9a7f-91f5e969d67f · outbound

This paper cites Going deeper with convolutions.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Going deeper with convolutions

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.901907Z

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.

Observation 7dbc9ced-08d0-4b58-8c48-c27f50ec19d4 · outbound

This paper cites A genetic programming approach to designing convolutional neural network architectures.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation A genetic programming approach to designing convolutional neural network architectures

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.903658Z

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.

Observation 5bde79de-1bb3-410a-ace1-c2bb40bcb271 · outbound

This paper cites A survey on evolutionary neural architecture search.IEEE transactions on neural networks and learning systems, 2021.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation A survey on evolutionary neural architecture search.IEEE transactions on neural networks and learning systems, 2021

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.909289Z

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.

Observation c8986f66-862a-48bc-87ef-fd723d9ccdfa · outbound

This paper cites Neural Architecture Search with Reinforcement Learning.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Neural Architecture Search with Reinforcement Learning

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-07-09T04:35:57.547037Z

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.

Observation fb0a50bd-2ea6-4edc-af2a-432afe8bb1c9 · outbound

This paper cites Random search and reproducibility for neural architecture search.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Random search and reproducibility for neural architecture search

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.900166Z

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.

Observation a0d19498-bf0e-46d9-aeb6-ba2ae34e1db5 · outbound

This paper cites Node splitting: A constructive algorithm for feed-forward neural networks.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Node splitting: A constructive algorithm for feed-forward neural networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.911502Z

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.

Observation b250d378-4c49-4d5f-abcf-2d975b75b51a · outbound

This paper cites GradMax: Growing Neural Networks using Gradient Information.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation GradMax: Growing Neural Networks using Gradient Information

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-09T04:35:57.533655Z

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.

Observation 7bbab5d3-31ce-46f3-9bab-0cf5b1edf6a2 · outbound

This paper cites Firefly neural architecture descent: a general approach for growing neural networks.Advances in neural information processing systems, 33:22373–22383, 2020.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Firefly neural architecture descent: a general approach for growing neural networks.Advances in neural information processing systems, 33:22373–22383, 2020

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.905675Z

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.

Observation 0218d676-1c9d-4da0-96bc-38f93d175d7a · outbound

This paper cites Topological derivative approach for deep neural network architecture adaptation.arXiv preprint arXiv:2502.06885, 2025.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Topological derivative approach for deep neural network architecture adaptation.arXiv preprint arXiv:2502.06885, 2025

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-09T04:35:57.536776Z

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.

Observation da4f95c5-9932-439e-aae5-f1b2fe3c1fd3 · outbound

This paper cites An adaptive and stability-promoting layerwise training approach for sparse deep neural network architecture.Computer Methods in Applied Mechanics and Engineering, 441:117938, 2025.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation An adaptive and stability-promoting layerwise training approach for sparse deep neural network architecture.Computer Methods in Applied Mechanics and Engineering, 441:117938, 2025

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.916530Z

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.

Observation 12ce60f7-cf66-4900-9335-09e10f6a8ffc · outbound

This paper cites Splitting steepest descent for growing neural architectures.Advances in neural information processing systems, 32, 2019.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Splitting steepest descent for growing neural architectures.Advances in neural information processing systems, 32, 2019

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.934159Z

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.

Observation a35cb5ed-9ec9-44ac-a752-bd006fdb2fc1 · outbound

This paper cites Greedy layer-wise training of deep networks.Advances in neural information processing systems, 19, 2006.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Greedy layer-wise training of deep networks.Advances in neural information processing systems, 19, 2006

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.936007Z

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.

Observation 5bbf92ad-fc06-4e66-97ec-28002d5867df · outbound

This paper cites Forward Thinking: Building and Training Neural Networks One Layer at a Time.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Forward Thinking: Building and Training Neural Networks One Layer at a Time

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-09T04:35:57.542179Z

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.

Observation 4ac569aa-1ed1-414f-8abf-94f37ff639ae · outbound

This paper cites Net2Net: Accelerating Learning via Knowledge Transfer.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Net2Net: Accelerating Learning via Knowledge Transfer

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-07-09T04:35:57.544585Z

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.

Observation 30d19827-c5e8-4260-b662-df15d341ddca · outbound

This paper cites SensLI: Sensitivity-Based Layer Insertion for Neural Networks.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation SensLI: Sensitivity-Based Layer Insertion for Neural Networks

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-07-09T04:35:57.549417Z

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.

Observation 7ec281e1-5045-4cc6-be36-c22aa831cd97 · outbound

This paper cites An optimal control approach to deep learning and applications to discrete-weight neural networks.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation An optimal control approach to deep learning and applications to discrete-weight neural networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.924941Z

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.

Observation b1b2ad61-5273-4f62-a44c-3ae96dcbba88 · outbound

This paper cites Neural ordinary differential equations.Advances in neural information processing systems, 31.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Neural ordinary differential equations.Advances in neural information processing systems, 31

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.926778Z

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.

Observation 0de11ab2-854c-40b4-a876-42568d300e17 · outbound

This paper cites An optimal control approach to a posteriori error estimation in finite element methods.Acta numerica, 10:1–102, 2001.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation An optimal control approach to a posteriori error estimation in finite element methods.Acta numerica, 10:1–102, 2001

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.928688Z

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.

Observation 45e78aa5-11d2-4b1b-9f7f-42bdaa26b4f4 · outbound

This paper cites The dual weighted residuals approach to optimal control of ordinary differential equations.BIT Numerical Mathematics, 50(3):587–607, 2010.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation The dual weighted residuals approach to optimal control of ordinary differential equations.BIT Numerical Mathematics, 50(3):587–607, 2010

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.930511Z

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.

Observation e7aa217f-60f3-4368-92ad-adb9779c0ddb · outbound

This paper cites Deep residual learning for image recognition.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Deep residual learning for image recognition

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.932264Z

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.

Observation 93874226-f9ad-4f59-ade8-1631c8926cfa · outbound

This paper cites Deep learning as optimal control problems: models and numerical methods.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Deep learning as optimal control problems: models and numerical methods

Reference 24

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T04:35:57.539461Z

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.

Observation 668c4df0-cf81-4177-af9b-28917f3fd4a9 · outbound

This paper cites Explicit-in-time goal-oriented adaptivity.Computer Methods in Applied Mechanics and Engineering, 347:176–200, 2019.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Explicit-in-time goal-oriented adaptivity.Computer Methods in Applied Mechanics and Engineering, 347:176–200, 2019

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.921065Z

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.

Observation 5805988e-5a9b-42fe-b490-f7cbb87ab8be · outbound

This paper cites Numerical solution of the navier-stokes equations.Mathematics of computation, 22(104):745–762, 1968.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Numerical solution of the navier-stokes equations.Mathematics of computation, 22(104):745–762, 1968

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.923071Z

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.

Observation fb2d4c9b-546f-4668-b593-0d862ffd4c68 · outbound

This paper cites Springer, 2006.

An optimal control approach for neural network architecture adaptation with a posteriori error estimation Springer, 2006

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T04:35:57.918928Z

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.

Pith citing papers

No inbound Pith citation observations are available.