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Paper Citation Record · LEDGER

Multi-ResNets for Subspace Preconditioning in Constrained Optimization

As of 8 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2606.06300.

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

pith.paper-citation-record.v1
2606.06300 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T01:47:11.255174Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

20 of 20 outbound references displayed

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  • verified fuzzy0
  • unresolved18
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  • malformed identifier0
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External citation measurements

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Outbound references

Observation 19e9d689-5deb-4338-a98a-f1ffc7491b95 · outbound

This paper cites Zico Kolter.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Zico Kolter

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 39613d17-da90-4910-a61f-c95510ee2d79 · outbound

This paper cites Nguyen and Priya L.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Nguyen and Priya L

Reference 2

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source=pdf_text observed=2026-06-28T01:47:11.255174Z digest=sha256:9554ce2139edca83787c962db02de8ca0e3a2a4703bee686b2ff8813e463c07d

Observation 9222480b-f201-4fcb-a80a-8d4266d601eb · outbound

This paper cites Zico Kolter.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Zico Kolter

Reference 3

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source=pdf_text observed=2026-06-28T01:47:11.255174Z digest=sha256:bcbac5f4ea3084e9d46591033eb7bb917f3ecdcee2e3b4b35f578b5b7f34cf67

Observation 45c3e18a-0efb-4c3a-a1c8-ff2f7a6aced9 · outbound

This paper cites Zico Kolter.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Zico Kolter

Reference 4

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Observation 0d50f256-5480-4569-90ad-bb157632a90c · outbound

This paper cites an unresolved cited work.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Unresolved cited work

Reference 5

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source=pdf_text observed=2026-06-28T01:47:11.255174Z digest=sha256:65810091525c366b50542f0aa6293affe847cc4a5349dbeca658f49729c5cfd2

Observation 841c2098-fa5b-46fd-af7e-8ff25bc80c8a · outbound

This paper cites QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints

Reference 6

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source=pdf_text observed=2026-06-28T01:47:11.255174Z digest=sha256:7fcfb113af17501dd704738e5fae857fcc0ea71d123fb93c70e486ed06be7f5d

Observation 1c2c1af6-6034-45d8-bdf2-2d37b3619117 · outbound

This paper cites an unresolved cited work.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Unresolved cited work

Reference 7

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Observation ed012a92-8241-4498-a353-b4b6e724eb66 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization U-net: Convolutional networks for biomedical image segmentation

Reference 8

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Observation d97f78a7-6bb4-4ee2-b1f9-5f7375ccb2e9 · outbound

This paper cites A unified framework for U-Net design and analysis.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization A unified framework for U-Net design and analysis

Reference 9

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Observation 75903658-a724-459d-82f6-f49ba9106028 · outbound

This paper cites A multi-resolution framework for u-nets with applications to hierarchical vaes.Advances in Neural Information Processing Systems, 35:15529–15544, 2022.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization A multi-resolution framework for u-nets with applications to hierarchical vaes.Advances in Neural Information Processing Systems, 35:15529–15544, 2022

Reference 10

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Observation c49cd827-b571-4c82-ba40-b7694cb2bc8f · outbound

This paper cites Hierarchical learning to solve pdes using physics-informed neural networks.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Hierarchical learning to solve pdes using physics-informed neural networks

Reference 11

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Unavailable: canonical work link unavailable.

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Observation 33b7e12e-6ba6-4992-8c6f-97e379b4ae85 · outbound

This paper cites Numerical solution of mixed- dimensional pdes using a neural preconditioner.Computers & Mathematics with Applications, 206:58–79, 2026.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Numerical solution of mixed- dimensional pdes using a neural preconditioner.Computers & Mathematics with Applications, 206:58–79, 2026

Reference 12

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Unavailable: canonical work link unavailable.

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Observation 1c3a1adb-3cf0-42ec-9d0e-160818e59333 · outbound

This paper cites Mesh-informed neural networks for operator learning in finite element spaces.Journal of Scientific Computing, 97(2):35, 2023.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Mesh-informed neural networks for operator learning in finite element spaces.Journal of Scientific Computing, 97(2):35, 2023

Reference 13

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Unavailable: canonical work link unavailable.

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Observation 65701b1e-75a4-4304-bb1d-d505708c0f12 · outbound

This paper cites Photographic image synthesis with cascaded refinement networks.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Photographic image synthesis with cascaded refinement networks

Reference 14

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Observation c79c87bc-7334-4f59-94a6-0b5bc13944bd · outbound

This paper cites Deep residual learning for im- age recognition.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Deep residual learning for im- age recognition

Reference 15

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Observation 967546ce-c9a4-41da-af0e-822c0efbacb7 · outbound

This paper cites Deep neural networks as gaussian processes.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Deep neural networks as gaussian processes

Reference 16

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Observation a4612204-7675-45b4-8356-3748452eb5cb · outbound

This paper cites Gaussian process behaviour in wide deep neural networks.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization Gaussian process behaviour in wide deep neural networks

Reference 17

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Unavailable: canonical work link unavailable.

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Observation bf7d318b-cf1f-4eed-a6c5-0203c0163d01 · outbound

This paper cites On lazy training in differentiable program- ming.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization On lazy training in differentiable program- ming

Reference 18

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Unavailable: canonical work link unavailable.

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Observation 1ae1771b-f4f4-4b6b-942a-bd423252922c · outbound

This paper cites The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms

Reference 19

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verified exact
arxiv_id, observed 2026-07-02T12:46:57.514467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a96042f7-aaa4-4677-82a7-45d76f712e4b · outbound

This paper cites PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow.

Multi-ResNets for Subspace Preconditioning in Constrained Optimization PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-02T12:46:57.517105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.