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Paper Citation Record · LEDGER

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries

As of 20 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 1 inbound Pith citation observation for arXiv:2502.01517.

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

pith.paper-citation-record.v1
2502.01517 v1

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:07:50.720771Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:18:04.371651Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T05:18:04.776183Z

Reference resolution

67 of 67 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 57bfdeb1-3161-4135-91b1-a62fea620fa1 · outbound

This paper cites Material extrusion additive manufacturing of multifunctional sandwich panels with load-bearing and acoustic capabilities for aerospace applications.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Material extrusion additive manufacturing of multifunctional sandwich panels with load-bearing and acoustic capabilities for aerospace applications

Reference 1

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c7264ad7-dd2c-42b6-a704-6037da3277c3 · outbound

This paper cites Review of additive manufacturing technologies and applications in the aerospace industry, pages 7–31.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Review of additive manufacturing technologies and applications in the aerospace industry, pages 7–31

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0f55a75b-89a9-430a-ab26-170765bd47b4 · outbound

This paper cites 3d printed different polymer fuel grains for hybrid rocket engine.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries 3d printed different polymer fuel grains for hybrid rocket engine

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 021671f2-96de-41ed-90a1-0217443a51f8 · outbound

This paper cites Fused deposition modeling for unmanned aerial vehicles (uavs): A review.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Fused deposition modeling for unmanned aerial vehicles (uavs): A review

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation fbf044fe-cca3-4d8a-a438-4fb187ec8753 · outbound

This paper cites Facile method for 3d printing conformally onto uneven surfaces and its application to face masks.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Facile method for 3d printing conformally onto uneven surfaces and its application to face masks

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 01b81fe9-9dd7-475d-9a4a-656771aba1f0 · outbound

This paper cites Additive manufacturing of cellulosic materials with robust mechanics and antimicrobial functionality.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Additive manufacturing of cellulosic materials with robust mechanics and antimicrobial functionality

Reference 6

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 2a405fbb-ff9a-45e5-87e5-abf51e7bc6e7 · outbound

This paper cites Additive manufacturing of biomechanically tailored meshes for compliant wearable and implantable devices.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Additive manufacturing of biomechanically tailored meshes for compliant wearable and implantable devices

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b8fef6b4-0e3f-477d-a34b-bd0f2642256a · outbound

This paper cites Reconfigurable aqueous 3d printing with adaptive dual locks.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Reconfigurable aqueous 3d printing with adaptive dual locks

Reference 8

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4b1db66c-66e7-4d34-b269-55ff85e72371 · outbound

This paper cites 3d printed patient-specific aortic root models with internal sensors for minimally invasive applications.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries 3d printed patient-specific aortic root models with internal sensors for minimally invasive applications

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 15e1dd16-9921-4faa-9718-de435b754d9f · outbound

This paper cites 3d printing of buildings and building components as the future of sustainable construction? Procedia Engineering, 151:292–299, 2016.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries 3d printing of buildings and building components as the future of sustainable construction? Procedia Engineering, 151:292–299, 2016

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9b608206-388b-4f2a-a5a3-04d7bfc94bb4 · outbound

This paper cites NASA Centennial Challenge: Three Dimensional (3D) Printed Habitat, pages 333–342.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries NASA Centennial Challenge: Three Dimensional (3D) Printed Habitat, pages 333–342

Reference 11

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation ff70b033-f65b-433e-abfa-30f17e5ae03a · outbound

This paper cites Additive manufacturing (3d printing): A review of materials, methods, applications and challenges.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Additive manufacturing (3d printing): A review of materials, methods, applications and challenges

Reference 12

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verified fuzzy
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Source-reported events for the cited work

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Observation 12249bea-f051-4c14-b01e-5ba86ccff2e8 · outbound

This paper cites Fused deposition modeling of thermoplastic elastomeric materials: Challenges and opportunities.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Fused deposition modeling of thermoplastic elastomeric materials: Challenges and opportunities

Reference 13

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 03de2b6e-9212-4b2f-87df-912226623e58 · outbound

This paper cites Optimization of fused deposition modeling process parameters: a review of current research and future prospects.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Optimization of fused deposition modeling process parameters: a review of current research and future prospects

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.307192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.545390Z digest=sha256:2c19a99940706fc3474147a892eeefb0c0af1341482d8322085013efa7685873

Observation e8b17f75-f46c-4d2e-84cf-1c7d9e5c577c · outbound

This paper cites Generalisable 3d printing error detection and correction via multi-head neural networks.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Generalisable 3d printing error detection and correction via multi-head neural networks

Reference 15

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 25b287cc-7b5d-455f-99e5-9d31c72a51b9 · outbound

This paper cites Quantitative and real-time control of 3d printing material flow through deep learning.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Quantitative and real-time control of 3d printing material flow through deep learning

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a3f56c9e-f341-4d93-8635-0c360f69880f · outbound

This paper cites Image analysis-based closed loop quality control for additive manufacturing with fused filament fabrication.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Image analysis-based closed loop quality control for additive manufacturing with fused filament fabrication

Reference 17

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 52b17b6e-8b8f-45a0-9b99-5be82e0f2ee5 · outbound

This paper cites Autonomous in-situ correction of fused deposition modeling printers using computer vision and deep learning.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Autonomous in-situ correction of fused deposition modeling printers using computer vision and deep learning

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c0e78f24-39e9-466f-8492-e8778212e36f · outbound

This paper cites Design for additive manufacturing: Trends, opportunities, considerations, and constraints.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Design for additive manufacturing: Trends, opportunities, considerations, and constraints

Reference 19

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Source-reported events for the cited work

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Observation 95e0f8a4-6330-41e6-855a-2f8c14198fa6 · outbound

This paper cites 3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries 3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a618bfdf-040e-4782-aea9-190010d7c7ff · outbound

This paper cites Gaussian splatting slam.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Gaussian splatting slam

Reference 21

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f1d873e7-95ee-4db0-a03a-d84a89bb24e5 · outbound

This paper cites S3cnet: A sparse semantic scene completion network for lidar point clouds.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries S3cnet: A sparse semantic scene completion network for lidar point clouds

Reference 22

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation abc9c232-4812-4963-84e7-f17ddab506c9 · outbound

This paper cites Geometric deep learning: Grids, groups, graphs, geodesics, and gauges, 2021.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Geometric deep learning: Grids, groups, graphs, geodesics, and gauges, 2021

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 288b16bc-2d0e-43c5-9e17-6e3c8020232f · outbound

This paper cites Graph neural network for traffic forecasting: A survey.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Graph neural network for traffic forecasting: A survey

Reference 24

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 1fabb70e-83da-4a4b-9dff-e6287388073d · outbound

This paper cites Stretchable e-skin and transformer enable high-resolution morphological reconstruction for soft robots.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Stretchable e-skin and transformer enable high-resolution morphological reconstruction for soft robots

Reference 25

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation e45cc051-60cf-4a70-a7e1-9f522580b44b · outbound

This paper cites Geometric deep learning for shape correspondence in mass customization by three-dimensional printing.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Geometric deep learning for shape correspondence in mass customization by three-dimensional printing

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation dae86dee-5ea8-48c8-8a51-d1de603fd674 · outbound

This paper cites Learning mesh-based simulation with graph networks, 2021.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Learning mesh-based simulation with graph networks, 2021

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.184568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 39781077-7fe0-4f65-b72d-f14c1076fcdc · outbound

This paper cites 3d representation methods: A survey, 2024.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries 3d representation methods: A survey, 2024

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 66b02888-a0fc-4491-b778-82e81446c06b · outbound

This paper cites Joint implicit neural representation for high-fidelity and compact vector fonts.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Joint implicit neural representation for high-fidelity and compact vector fonts

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.594714Z digest=sha256:6f139b6af36a123b435ee711821b4b06a3acf3c2e739a9f993c4ab46adbf3eb6

Observation c4271d32-a704-415e-9b0d-d1e4330e816e · outbound

This paper cites Neural geometric level of detail: Real-time rendering with implicit 3d shapes, 2021.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Neural geometric level of detail: Real-time rendering with implicit 3d shapes, 2021

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.154576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 01fbe5d7-9d33-4306-98a7-e53eaeec7cf9 · outbound

This paper cites Learning continuous image representation with local implicit image function, 2021.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Learning continuous image representation with local implicit image function, 2021

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.144117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a843b039-9f3c-42e8-a4ac-864ec5e967b3 · outbound

This paper cites A multi-implicit neural representation for fonts, 2022.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries A multi-implicit neural representation for fonts, 2022

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.133694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 3e965ffa-17fd-475b-8598-90ca12ea1689 · outbound

This paper cites Exploring the performance of implicit neural representations for brain image registration.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Exploring the performance of implicit neural representations for brain image registration

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.123655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.606319Z digest=sha256:e047ec34627b73fe5f716af95cf3195b0bece4bce7b2d1002a698e4c29447ee9

Observation 54f4db27-c71b-4714-89cd-952e0e19f63a · outbound

This paper cites Freenerf: Improving few-shot neural rendering with free frequency regularization, 2023.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Freenerf: Improving few-shot neural rendering with free frequency regularization, 2023

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.113461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.609501Z digest=sha256:1944d7665869fac7fd4154ad8d4905987d52bece2acaf57e0bca27a0d7d5f00e

Observation 84388aec-a0da-44e4-9a58-042e70741bf6 · outbound

This paper cites Bundlesdf: Neural 6-dof tracking and 3d reconstruction of unknown objects, 2023.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Bundlesdf: Neural 6-dof tracking and 3d reconstruction of unknown objects, 2023

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.103539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.612982Z digest=sha256:29334374272e8a9d14dc1a30c28600ad1847ba84ec4994cd5f39786501ea3d2c

Observation 750de2e4-24c8-490e-b542-a2b142f352c0 · outbound

This paper cites isdf: Real-time neural signed distance fields for robot perception, 2022.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries isdf: Real-time neural signed distance fields for robot perception, 2022

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.094565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.616176Z digest=sha256:274024aab61afd88ab9943d6b0db6dbbdf3b269e35622ee9e625c7ec37e52485

Observation f6df254d-6cb2-40a0-a271-339fea4add27 · outbound

This paper cites Shapo: Implicit representations for multi-object shape, appearance, and pose optimization, 2022.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Shapo: Implicit representations for multi-object shape, appearance, and pose optimization, 2022

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.085809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.619459Z digest=sha256:d68716cb0a11766a401955a968124a0ca060ac9f5ff01124ee78a4b55983d855

Observation 33a7fdd1-e7b5-4c23-ad83-1d78adc54702 · outbound

This paper cites ilabel: Revealing objects in neural fields.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries ilabel: Revealing objects in neural fields

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.077390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.622600Z digest=sha256:4ce56ecaec3f2b2777635d9419825ff434297c5204a745913890026f0cb615aa

Observation a7af0546-321b-4e46-b554-d710a2962e9b · outbound

This paper cites Feature-realistic neural fusion for real-time, open set scene understanding.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Feature-realistic neural fusion for real-time, open set scene understanding

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.068337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.625818Z digest=sha256:23fa8420078538f2465b3e520081744eb98994670bb58ef274dc2489bcca7a77

Observation 93823307-4c89-4345-a616-3d36d073b7f1 · outbound

This paper cites Physics informed deep learning for computational elastodynamics without labeled data, 2020.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Physics informed deep learning for computational elastodynamics without labeled data, 2020

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.058689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.629288Z digest=sha256:f6c7ccf0ef314d63a7c249ce8f66fd224dac3de9e79155e6304ad9e8890b6509

Observation d603fa78-d712-41ce-879e-1a3bef5f7655 · outbound

This paper cites Nsfnets (navier-stokes flow nets): Physics- informed neural networks for the incompressible navier-stokes equations.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Nsfnets (navier-stokes flow nets): Physics- informed neural networks for the incompressible navier-stokes equations

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.049012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.632767Z digest=sha256:c8996c5db57002abcbe98fb547dbb3738e3bdd36c6cf169ba375fd6ade29df2d

Observation db799d06-4631-4afc-8fc3-97a6aac4739c · outbound

This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.038605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.636272Z digest=sha256:74940a777723c38bbffb8185de9e31c86259b29d617f2341a4622976ba85a11c

Observation d8bfdd2d-c10c-4347-8c68-dc2f1ea8cdc4 · outbound

This paper cites Implicit neural representations with periodic activation functions, 2020.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Implicit neural representations with periodic activation functions, 2020

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.028156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.639773Z digest=sha256:92cc5f5980fa4afd91fc098a0bfb51085a5ea595cca3390cd852c4e792efca45

Observation 76145a46-9d51-46a7-8ebe-c42d7e333e85 · outbound

This paper cites Compositional pattern producing networks : A novel abstraction of development.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Compositional pattern producing networks : A novel abstraction of development

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.017855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.643223Z digest=sha256:9debe385e39cb6478e42be6a68a613887107ef6148a5cd966fb6e2b881a15c2e

Observation 4fa2ebd0-0e45-4000-b3c1-a9066c205ffe · outbound

This paper cites Inras: Implicit neural representation for audio scenes.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Inras: Implicit neural representation for audio scenes

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:51.007241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.646914Z digest=sha256:60ca13bd18893fb4610d6d364b726e555c2753a762f13260e6edb5105bcffb04

Observation 2c50475d-e585-4ec4-8b6d-0260809d9472 · outbound

This paper cites Hypersound: Generat- ing implicit neural representations of audio signals with hypernetworks, 2024.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Hypersound: Generat- ing implicit neural representations of audio signals with hypernetworks, 2024

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.996534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.650308Z digest=sha256:fedc9f537f35bcd300d559e9bbb7de8ebe4f5b9674817184efb54206da987d75

Observation 2b851c48-3ea6-4acd-ab9b-90d240901927 · outbound

This paper cites Meshfreeflownet: A physics-constrained deep continuous space-time super-resolution framework, 2020.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Meshfreeflownet: A physics-constrained deep continuous space-time super-resolution framework, 2020

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.986455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.653584Z digest=sha256:8c2179e826e538e673130cce55b9a55d169de5b74a6967e7d1217f830ab46249

Observation 03ddd50c-c6cb-41b9-adef-65cdb27d3f84 · outbound

This paper cites Implicit geometric regularization for learning shapes, 2020.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Implicit geometric regularization for learning shapes, 2020

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.976039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.656901Z digest=sha256:548f3d7c63137fb2969b8d910d6200438af696b626a7778cf3938d66fed23024

Observation c2820e82-f3b5-4e32-89f3-1b7b57ff2539 · outbound

This paper cites Neural descriptor fields: Se(3)-equivariant object representations for manipulation, 2021.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Neural descriptor fields: Se(3)-equivariant object representations for manipulation, 2021

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.964646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.660012Z digest=sha256:b2cd65c6f4f9826f52057e22e3fef83b49c1e0475a46bbd31f9b5870526f07a3

Observation ed6a1b6d-d43c-4597-ab31-fef21bc2462a · outbound

This paper cites Capturing dynamical correlations using implicit neural representations.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Capturing dynamical correlations using implicit neural representations

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.952571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.663298Z digest=sha256:573c5c02142f6c5c9639bf3eadbbb8b31142f9e865e669aec1d4891519973f41

Observation e7d1a698-5045-405d-89fc-9e7a78dc8b08 · outbound

This paper cites Occupancy networks: Learning 3d reconstruction in function space, 2019.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Occupancy networks: Learning 3d reconstruction in function space, 2019

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.941202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.666824Z digest=sha256:3f144ab2e97aa1688d6593b72fc9d84821320f457a47f8ba1e69961b1308625c

Observation a0ba69a0-d8c4-4dba-bfba-15b8a648c7fd · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape representation, 2019.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Deepsdf: Learning continuous signed distance functions for shape representation, 2019

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.931093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.669939Z digest=sha256:376af83bd6dcab4f0e8021b21a0dc2b9d844fa1380d1fb6775914f600589e01b

Observation ed4655d9-58ec-4408-b887-abbc0fc8608e · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis, 2020.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Nerf: Representing scenes as neural radiance fields for view synthesis, 2020

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.921353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.673100Z digest=sha256:1a252638a29909b128ba99cc9f023d3d8f474aa52558fdb0bbe4141b55c3456a

Observation ab7976a6-ca2d-43f6-855e-e85964ee255c · outbound

This paper cites Fourier features let networks learn high frequency functions in low dimensional domains, 2020.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Fourier features let networks learn high frequency functions in low dimensional domains, 2020

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.910786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.676874Z digest=sha256:f4fe3b12e65b4fa3aa04f566d45126637c0d106871ec30262da8ae8751c5cbdd

Observation 99173799-472a-4da9-9b0b-f490b395c849 · outbound

This paper cites Plenoctrees for real-time rendering of neural radiance fields, 2021.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Plenoctrees for real-time rendering of neural radiance fields, 2021

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-09T15:07:50.680341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:07:50.680341Z digest=sha256:4a2e8bd95f21e852d4e438741e10e65874ff23e0612c2ea8dd2a842fe329ecb3

Observation cfb7fd62-a3fe-4ce0-85b3-7db3cedad4ae · outbound

This paper cites Acorn: Adaptive coordinate networks for neural scene representation, 2021.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Acorn: Adaptive coordinate networks for neural scene representation, 2021

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.892077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.683565Z digest=sha256:dabc861b554d1aba006474405e6f245074a03ab91a5b0e6a6f7c21a478a358bd

Observation 964f7b64-20bf-4d76-9ff3-ce487e04770f · outbound

This paper cites Instant neural graphics primitives with a multiresolution hash encoding.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Instant neural graphics primitives with a multiresolution hash encoding

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.880926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.687058Z digest=sha256:0b519a8aba3109a6f5e3131a985d7c1fb78828e8e1a71417c8b62f1722eb6edb

Observation 3c0ffc66-4cea-4dff-87b2-27a47c452e1d · outbound

This paper cites Neural fields in visual computing and beyond.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Neural fields in visual computing and beyond

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.868913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.690690Z digest=sha256:6d170645a06d5a20f16deb36a121256f272b485f283570a2477102979901ca97

Observation 43ee1c78-f22f-4903-bb9d-ad79efaaee5a · outbound

This paper cites Learning smooth neural functions via lipschitz regularization.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Learning smooth neural functions via lipschitz regularization

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.858102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.694094Z digest=sha256:084366138bd2417e6c069b33d43f3d6c0e2507b7e8382d3a28c8d246cbb661d3

Observation 565d6177-6532-4ca6-a7fc-2ddde718f2f3 · outbound

This paper cites Double backpropagation increasing generalization performance.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Double backpropagation increasing generalization performance

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.846100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.697268Z digest=sha256:7bd0af9dc91ba3d8cc93cece67c06de431987cd1689a447739705c3ac8c29843

Observation e5314199-8131-43b7-85a9-4ec173f3e7ca · outbound

This paper cites Robustness via curvature regularization, and vice versa.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Robustness via curvature regularization, and vice versa

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.835009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.700677Z digest=sha256:083bf49086c7c6a398e8071526a81c7b545a03fb28d115833f6f37778590b47c

Observation d1b2a90e-bea6-4909-98bb-7bc0eec61c95 · outbound

This paper cites Intuitive Shape Editing in Latent Space.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Intuitive Shape Editing in Latent Space

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-08-09T15:07:50.756116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.703890Z digest=sha256:feb784ea89d75e2dd909de4b7511a3b663c696e76fd63016bbbc28986fe5a045

Observation a81c0b0a-6339-42f7-be15-828787bd718e · outbound

This paper cites Frame interpolation in video stream using optical flow methods.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Frame interpolation in video stream using optical flow methods

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.823069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.707633Z digest=sha256:e3eb9438d8141227a4371f70e59fc93e7d655f18fb82023c9677244178792064

Observation 0e60e710-8aec-4aa3-a59a-8dde6e57500a · outbound

This paper cites Automatic differentiation in pytorch.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Automatic differentiation in pytorch

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-09T15:07:50.711117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:07:50.711117Z digest=sha256:e88f02aa1aa43dad8ea831199c7d7c60ad5acfc2ccb6c1f1b66def947276f663

Observation 899767ca-c042-4631-969a-42f562f844d2 · outbound

This paper cites Marching cubes: A high resolution 3d surface construction algorithm.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Marching cubes: A high resolution 3d surface construction algorithm

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.803856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.714468Z digest=sha256:e5201af5957455c912f059065b9bb2cce83e2edc7765a34a0b17663dcd000a7d

Observation f864a036-6b1f-404c-9b64-d808ba611938 · outbound

This paper cites Ntopo: Mesh-free topology optimization using implicit neural representations, 2021.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Ntopo: Mesh-free topology optimization using implicit neural representations, 2021

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.792463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.717549Z digest=sha256:f7dfc3fb1703503b631ad708e77f7b5a5d84509f3f494e35fcbd5f8d6c17f3de

Observation 3376bb83-1a25-47e2-a8cc-a5532ac53704 · outbound

This paper cites Nito: Neural implicit fields for resolution-free topology optimization, 2024.

Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Nito: Neural implicit fields for resolution-free topology optimization, 2024

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:07:50.781576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T15:07:50.720771Z digest=sha256:95942d1e646dbfe3a80162a10754530e3790265e2701265d60cbec623f71de6b

Pith citing papers

Observation 12ad6bc4-8665-4da6-aef9-b22691a4f938 · inbound

Hybrid Reasoning for Perception, Explanation, and Autonomous Action in Manufacturing cites this paper.

Hybrid Reasoning for Perception, Explanation, and Autonomous Action in Manufacturing Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:18:04.782600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T05:18:04.371651Z digest=sha256:7fb9b403eaee541aa097f6079f0201ecc6f3095446c40f8c3f6aa94dd45b816a