Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T15:07:50.720771Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T15:07:50.720771Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:18:04.371651Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T05:18:04.776183Z
67 of 67 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 57bfdeb1-3161-4135-91b1-a62fea620fa1 · outbound
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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Observation c7264ad7-dd2c-42b6-a704-6037da3277c3 · outbound
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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Observation 0f55a75b-89a9-430a-ab26-170765bd47b4 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries 3d printed different polymer fuel grains for hybrid rocket engine
Reference 3
Source-reported events for the cited work
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Observation 021671f2-96de-41ed-90a1-0217443a51f8 · outbound
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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Observation fbf044fe-cca3-4d8a-a438-4fb187ec8753 · outbound
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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Observation 01b81fe9-9dd7-475d-9a4a-656771aba1f0 · outbound
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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Observation 2a405fbb-ff9a-45e5-87e5-abf51e7bc6e7 · outbound
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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Observation b8fef6b4-0e3f-477d-a34b-bd0f2642256a · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Reconfigurable aqueous 3d printing with adaptive dual locks
Reference 8
Source-reported events for the cited work
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Observation 4b1db66c-66e7-4d34-b269-55ff85e72371 · outbound
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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Observation 15e1dd16-9921-4faa-9718-de435b754d9f · outbound
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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Observation 9b608206-388b-4f2a-a5a3-04d7bfc94bb4 · outbound
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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Observation ff70b033-f65b-433e-abfa-30f17e5ae03a · outbound
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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Observation 12249bea-f051-4c14-b01e-5ba86ccff2e8 · outbound
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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Observation 03de2b6e-9212-4b2f-87df-912226623e58 · outbound
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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Observation e8b17f75-f46c-4d2e-84cf-1c7d9e5c577c · outbound
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
Source-reported events for the cited work
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Observation 25b287cc-7b5d-455f-99e5-9d31c72a51b9 · outbound
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
Source-reported events for the cited work
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Observation a3f56c9e-f341-4d93-8635-0c360f69880f · outbound
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
Source-reported events for the cited work
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Observation 52b17b6e-8b8f-45a0-9b99-5be82e0f2ee5 · outbound
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
Source-reported events for the cited work
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Observation c0e78f24-39e9-466f-8492-e8778212e36f · outbound
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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Observation 95e0f8a4-6330-41e6-855a-2f8c14198fa6 · outbound
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
Source-reported events for the cited work
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Observation a618bfdf-040e-4782-aea9-190010d7c7ff · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Gaussian splatting slam
Reference 21
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Observation f1d873e7-95ee-4db0-a03a-d84a89bb24e5 · outbound
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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Observation abc9c232-4812-4963-84e7-f17ddab506c9 · outbound
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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Observation 288b16bc-2d0e-43c5-9e17-6e3c8020232f · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Graph neural network for traffic forecasting: A survey
Reference 24
Source-reported events for the cited work
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Observation 1fabb70e-83da-4a4b-9dff-e6287388073d · outbound
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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Observation e45cc051-60cf-4a70-a7e1-9f522580b44b · outbound
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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Observation dae86dee-5ea8-48c8-8a51-d1de603fd674 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Learning mesh-based simulation with graph networks, 2021
Reference 27
Source-reported events for the cited work
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Observation 39781077-7fe0-4f65-b72d-f14c1076fcdc · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries 3d representation methods: A survey, 2024
Reference 28
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Observation 66b02888-a0fc-4491-b778-82e81446c06b · outbound
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
Source-reported events for the cited work
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Observation c4271d32-a704-415e-9b0d-d1e4330e816e · outbound
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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Observation 01fbe5d7-9d33-4306-98a7-e53eaeec7cf9 · outbound
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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Observation a843b039-9f3c-42e8-a4ac-864ec5e967b3 · outbound
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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Observation 3e965ffa-17fd-475b-8598-90ca12ea1689 · outbound
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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Observation 54f4db27-c71b-4714-89cd-952e0e19f63a · outbound
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
Source-reported events for the cited work
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Observation 84388aec-a0da-44e4-9a58-042e70741bf6 · outbound
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
Source-reported events for the cited work
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Observation 750de2e4-24c8-490e-b542-a2b142f352c0 · outbound
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
Source-reported events for the cited work
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Observation f6df254d-6cb2-40a0-a271-339fea4add27 · outbound
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
Source-reported events for the cited work
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Observation 33a7fdd1-e7b5-4c23-ad83-1d78adc54702 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries ilabel: Revealing objects in neural fields
Reference 38
Source-reported events for the cited work
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Observation a7af0546-321b-4e46-b554-d710a2962e9b · outbound
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
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Observation 93823307-4c89-4345-a616-3d36d073b7f1 · outbound
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
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Observation d603fa78-d712-41ce-879e-1a3bef5f7655 · outbound
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
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Observation db799d06-4631-4afc-8fc3-97a6aac4739c · outbound
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
Source-reported events for the cited work
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Observation d8bfdd2d-c10c-4347-8c68-dc2f1ea8cdc4 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Implicit neural representations with periodic activation functions, 2020
Reference 43
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Observation 76145a46-9d51-46a7-8ebe-c42d7e333e85 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Compositional pattern producing networks : A novel abstraction of development
Reference 44
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Observation 4fa2ebd0-0e45-4000-b3c1-a9066c205ffe · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Inras: Implicit neural representation for audio scenes
Reference 45
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Observation 2c50475d-e585-4ec4-8b6d-0260809d9472 · outbound
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
Source-reported events for the cited work
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Observation 2b851c48-3ea6-4acd-ab9b-90d240901927 · outbound
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
Source-reported events for the cited work
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Observation 03ddd50c-c6cb-41b9-adef-65cdb27d3f84 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Implicit geometric regularization for learning shapes, 2020
Reference 48
Source-reported events for the cited work
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Observation c2820e82-f3b5-4e32-89f3-1b7b57ff2539 · outbound
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
Source-reported events for the cited work
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Observation ed6a1b6d-d43c-4597-ab31-fef21bc2462a · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Capturing dynamical correlations using implicit neural representations
Reference 50
Source-reported events for the cited work
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Observation e7d1a698-5045-405d-89fc-9e7a78dc8b08 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Occupancy networks: Learning 3d reconstruction in function space, 2019
Reference 51
Source-reported events for the cited work
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Observation a0ba69a0-d8c4-4dba-bfba-15b8a648c7fd · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Deepsdf: Learning continuous signed distance functions for shape representation, 2019
Reference 52
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Observation ed4655d9-58ec-4408-b887-abbc0fc8608e · outbound
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
Source-reported events for the cited work
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Observation ab7976a6-ca2d-43f6-855e-e85964ee255c · outbound
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
Source-reported events for the cited work
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Observation 99173799-472a-4da9-9b0b-f490b395c849 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Plenoctrees for real-time rendering of neural radiance fields, 2021
Reference 55
Source-reported events for the cited work
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Observation cfb7fd62-a3fe-4ce0-85b3-7db3cedad4ae · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Acorn: Adaptive coordinate networks for neural scene representation, 2021
Reference 56
Source-reported events for the cited work
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Observation 964f7b64-20bf-4d76-9ff3-ce487e04770f · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Instant neural graphics primitives with a multiresolution hash encoding
Reference 57
Source-reported events for the cited work
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Observation 3c0ffc66-4cea-4dff-87b2-27a47c452e1d · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Neural fields in visual computing and beyond
Reference 58
Source-reported events for the cited work
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Observation 43ee1c78-f22f-4903-bb9d-ad79efaaee5a · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Learning smooth neural functions via lipschitz regularization
Reference 59
Source-reported events for the cited work
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Observation 565d6177-6532-4ca6-a7fc-2ddde718f2f3 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Double backpropagation increasing generalization performance
Reference 60
Source-reported events for the cited work
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Observation e5314199-8131-43b7-85a9-4ec173f3e7ca · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Robustness via curvature regularization, and vice versa
Reference 61
Source-reported events for the cited work
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Observation d1b2a90e-bea6-4909-98bb-7bc0eec61c95 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Intuitive Shape Editing in Latent Space
Reference 62
Source-reported events for the cited work
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Observation a81c0b0a-6339-42f7-be15-828787bd718e · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Frame interpolation in video stream using optical flow methods
Reference 63
Source-reported events for the cited work
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Observation 0e60e710-8aec-4aa3-a59a-8dde6e57500a · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Automatic differentiation in pytorch
Reference 64
Source-reported events for the cited work
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Observation 899767ca-c042-4631-969a-42f562f844d2 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Marching cubes: A high resolution 3d surface construction algorithm
Reference 65
Source-reported events for the cited work
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Observation f864a036-6b1f-404c-9b64-d808ba611938 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Ntopo: Mesh-free topology optimization using implicit neural representations, 2021
Reference 66
Source-reported events for the cited work
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Observation 3376bb83-1a25-47e2-a8cc-a5532ac53704 · outbound
Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries Nito: Neural implicit fields for resolution-free topology optimization, 2024
Reference 67
Source-reported events for the cited work
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Observation 12ad6bc4-8665-4da6-aef9-b22691a4f938 · inbound
Hybrid Reasoning for Perception, Explanation, and Autonomous Action in Manufacturing Regularized interpolation in 4D neural fields enables optimization of 3D printed geometries
Reference 33
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.