Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries | Paper Citation Record

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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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

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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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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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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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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

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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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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

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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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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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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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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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