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Paper Citation Record · LEDGER

Variational volume reconstruction with the Deep Ritz Method

As of 21 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2508.08309.

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

pith.paper-citation-record.v1
2508.08309 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:40:13.115598Z

measured 49 of 49 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 2026-08-02T23:34:48.867421Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

  • verified exact6
  • verified fuzzy32
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f85a2de9-37ff-4cfa-bd55-3ac407a33d2c · outbound

This paper cites A deep learning energy method for hyperelasticity and viscoelasticity.

Variational volume reconstruction with the Deep Ritz Method A deep learning energy method for hyperelasticity and viscoelasticity

Reference 1

Resolution
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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=arxiv_source observed=2026-08-05T22:40:09.097985Z digest=sha256:d11dd74e9f07d73a3f1c7b5fa7fea2e6c274e01ff6a22255f54c2d278b9403e0

Observation e00f914c-0110-40fb-9ed4-64ec2644f225 · outbound

This paper cites Arigovindan, M.

Variational volume reconstruction with the Deep Ritz Method Arigovindan, M

Reference 2

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verified fuzzy
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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 efe5aba9-3283-4d1c-910f-f6768c2c3691 · outbound

This paper cites Three-dimensional reconstruction of complex shapes based on the Delaunay triangulation.

Variational volume reconstruction with the Deep Ritz Method Three-dimensional reconstruction of complex shapes based on the Delaunay triangulation

Reference 3

Resolution
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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 81c5001d-1737-4c4a-b2d8-02c876315832 · outbound

This paper cites Volume Reconstruction from Slices.

Variational volume reconstruction with the Deep Ritz Method Volume Reconstruction from Slices

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-05T22:40:09.274623Z digest=sha256:0c63223417b47a88b6076ac209f9712513a6c2d0b09137cc63b99c0e42e3ac16

Observation 82371950-8284-461e-b292-f9206c3ba5e2 · outbound

This paper cites Learning phase field mean curvature flows with neural networks.

Variational volume reconstruction with the Deep Ritz Method Learning phase field mean curvature flows with neural networks

Reference 5

Resolution
verified exact
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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 3968f739-e61f-4365-9101-aed980d98861 · outbound

This paper cites A penalized Allen-Cahn equation for the mean curvature flow of thin structures.

Variational volume reconstruction with the Deep Ritz Method A penalized Allen-Cahn equation for the mean curvature flow of thin structures

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:40:09.421273Z digest=sha256:45bf167a2b77148bc7b2507560e394cc07530bb9233dface3d806807d8f443ff

Observation 6d3cfe85-b63e-4d44-bda9-f4271005502a · outbound

This paper cites Variational image segmentation model coupled with image restoration achievements.

Variational volume reconstruction with the Deep Ritz Method Variational image segmentation model coupled with image restoration achievements

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.858603Z

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=arxiv_source observed=2026-08-05T22:40:09.505348Z digest=sha256:8c8faf6d2b7e67c4d7957bb57d26c840fd271fdbb75ec82a4ee221bba5dfbe11

Observation 6783c5f7-ba40-46ba-84d1-40cf1a596d89 · outbound

This paper cites an unresolved cited work.

Variational volume reconstruction with the Deep Ritz Method Unresolved cited work

Reference 8

Resolution
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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 efb4c909-7206-491a-9ae6-a7f8ebde6ca8 · outbound

This paper cites Introduction to variational image-processing models and applications.

Variational volume reconstruction with the Deep Ritz Method Introduction to variational image-processing models and applications

Reference 9

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no resolver link, observed 2026-08-05T22:40:09.667055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:40:09.667055Z digest=sha256:0ff6d0773bc719ea490f0d5319b1edbeb555b6f5df0a48b79d4f13123cf44676

Observation 1a9ed17e-3848-49ee-bfa8-4803b2b7ea1f · outbound

This paper cites Existence of equilibria for the cahn-hilliard equation via local minimizers of the perimeter.

Variational volume reconstruction with the Deep Ritz Method Existence of equilibria for the cahn-hilliard equation via local minimizers of the perimeter

Reference 10

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verified exact
doi, observed 2026-08-05T22:40:13.154566Z

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

source=arxiv_source observed=2026-08-05T22:40:09.739525Z digest=sha256:54667b7018407583f28a88ec2bbff29a0954c57cbc52c9b0a9c830f3d45c3fc9

Observation df10f5b1-65f3-4e52-a32a-a767a29f4e95 · outbound

This paper cites Surface Reconstruction from Scattered Point via RBF Interpolation on GPU.

Variational volume reconstruction with the Deep Ritz Method Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:40:13.313081Z

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=arxiv_source observed=2026-08-05T22:40:09.830156Z digest=sha256:b8fe1d99a10d8c2eeb5ec6029aa8ee961b56fcd86365bb31be4a59b9a8edd8d6

Observation b3fb651f-2b33-4768-bc7c-711d9cb5f7a1 · outbound

This paper cites Surface Reconstruction from Sparse and Mutually Intersected Contours for Freehand 3D Ultrasound Using Variational Method.

Variational volume reconstruction with the Deep Ritz Method Surface Reconstruction from Sparse and Mutually Intersected Contours for Freehand 3D Ultrasound Using Variational Method

Reference 12

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 0df2f3f3-1461-49cb-88f9-c59f00397b21 · outbound

This paper cites Image Super-Resolution Using Deep Convolutional Networks.

Variational volume reconstruction with the Deep Ritz Method Image Super-Resolution Using Deep Convolutional Networks

Reference 13

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no resolver link, observed 2026-08-05T22:40:10.006495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c27d3611-e021-44d7-9985-41930c1338d3 · outbound

This paper cites A level set formulation for Willmore flow.

Variational volume reconstruction with the Deep Ritz Method A level set formulation for Willmore flow

Reference 14

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 70c6d535-50bf-4fa8-b1a1-3f1a3868fa91 · outbound

This paper cites Super-resolution reconstruction of single anisotropic 3D MR images using residual convolutional neural network.

Variational volume reconstruction with the Deep Ritz Method Super-resolution reconstruction of single anisotropic 3D MR images using residual convolutional neural network

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.812205Z

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=arxiv_source observed=2026-08-05T22:40:10.146887Z digest=sha256:954a699311196759f9667bc5e86faf4404fccc46b49c5631ad9423590afd0b46

Observation a3fe1c0e-4784-4e5a-af38-736509c57da2 · outbound

This paper cites The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems.

Variational volume reconstruction with the Deep Ritz Method The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems

Reference 16

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unresolved
no resolver link, observed 2026-08-05T22:40:10.237745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:40:10.237745Z digest=sha256:16dd75831471bc49c1275d22c5d6e73f4119fccd86ae4c4a69045cdad6647999

Observation bf1bad7e-945c-41d9-9189-3fb3c63eb69d · outbound

This paper cites Miller, Harini Veeraraghavan, Bernd Freisleben, Alexandra J.

Variational volume reconstruction with the Deep Ritz Method Miller, Harini Veeraraghavan, Bernd Freisleben, Alexandra J

Reference 17

Resolution
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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 7b51389c-c899-4597-889f-6ddaf1233a3b · outbound

This paper cites Colliding Interfaces in Old and New Diffuse-interface Approximations of Willmore-flow.

Variational volume reconstruction with the Deep Ritz Method Colliding Interfaces in Old and New Diffuse-interface Approximations of Willmore-flow

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:40:13.257321Z

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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 a658eab1-35e4-4b78-a6f4-075d492a2947 · outbound

This paper cites an unresolved cited work.

Variational volume reconstruction with the Deep Ritz Method Unresolved cited work

Reference 19

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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 1823f1bc-5c41-456f-8407-48442f992df5 · outbound

This paper cites Jimack, and René de Borst.

Variational volume reconstruction with the Deep Ritz Method Jimack, and René de Borst

Reference 20

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verified fuzzy
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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 ec89911c-57b7-41c8-80db-f020372608f4 · outbound

This paper cites Giannakopoulos, Matthew J.

Variational volume reconstruction with the Deep Ritz Method Giannakopoulos, Matthew J

Reference 21

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 96709d6c-76eb-47e2-8369-d0cd8da6d1db · outbound

This paper cites A simple shape transformation method based on phase-field model.

Variational volume reconstruction with the Deep Ritz Method A simple shape transformation method based on phase-field model

Reference 22

Resolution
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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 08768486-0b9c-4e12-a20b-c547a87392b3 · outbound

This paper cites A Variational Approach for Volume -to- Slice Registration.

Variational volume reconstruction with the Deep Ritz Method A Variational Approach for Volume -to- Slice Registration

Reference 23

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

source=arxiv_source observed=2026-08-05T22:40:10.823838Z digest=sha256:bc3acfee1e3bd7d5f0b3df004d195bb76d5d73dcfe3d8ef557ea93e032188641

Observation 6ed39cde-938f-4b78-9d54-ff038e696803 · outbound

This paper cites an unresolved cited work.

Variational volume reconstruction with the Deep Ritz Method Unresolved cited work

Reference 24

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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 ddc27206-01c6-4291-9836-dd4a319f21e4 · outbound

This paper cites Osher, and R.

Variational volume reconstruction with the Deep Ritz Method Osher, and R

Reference 25

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=arxiv_source observed=2026-08-05T22:40:10.954464Z digest=sha256:d649ac2bd33cd30c0e4187f9447b1cc864b332f10ab19149d2ef97ae9e1805bb

Observation 1368cb6f-ba83-4c4e-92b3-8a10dc25b3e5 · outbound

This paper cites C1-continuous Terrain Reconstruction from Sparse Contours.

Variational volume reconstruction with the Deep Ritz Method C1-continuous Terrain Reconstruction from Sparse Contours

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.706025Z

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

source=arxiv_source observed=2026-08-05T22:40:11.009566Z digest=sha256:22831e128f9746f9c5a47db7eaf73bbeb8d667703b5c0c384b39560e220cada3

Observation eaac1a4b-77bf-48d8-86bc-10d9ef15945c · outbound

This paper cites Three-dimensional volume reconstruction from multi-slice data using a shape transformation.

Variational volume reconstruction with the Deep Ritz Method Three-dimensional volume reconstruction from multi-slice data using a shape transformation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.693926Z

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=arxiv_source observed=2026-08-05T22:40:11.123787Z digest=sha256:ced2f5ab03cace97717f9a576703f7c82d753caa7bdd46a04fbc37b80557af16

Observation ba34c7fc-74bc-4fc1-9f48-29d224069373 · outbound

This paper cites Accurate Surface Reconstruction in 3D Using Two -dimensional Parallel Cross Sections.

Variational volume reconstruction with the Deep Ritz Method Accurate Surface Reconstruction in 3D Using Two -dimensional Parallel Cross Sections

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.681263Z

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=arxiv_source observed=2026-08-05T22:40:11.245155Z digest=sha256:e569bf058b9cbf74abee4b37d85ba82bee2251e71d66b0d39d1a2fd7a7133ef4

Observation 07d559a1-3c8c-40bb-bec3-9a3a86bdcc6c · outbound

This paper cites An efficient volume repairing method by using a modified Allen - Cahn equation.

Variational volume reconstruction with the Deep Ritz Method An efficient volume repairing method by using a modified Allen - Cahn equation

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.669082Z

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=arxiv_source observed=2026-08-05T22:40:11.374204Z digest=sha256:0187870900a4cc1bb37aa695460c17b2412b6741c381519838b9fad4d15cc501

Observation 12c58a5d-3f1f-4ee4-8fac-54ab1684a687 · outbound

This paper cites Three-dimensional volume reconstruction from slice data using phase-field models.

Variational volume reconstruction with the Deep Ritz Method Three-dimensional volume reconstruction from slice data using phase-field models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.657025Z

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=arxiv_source observed=2026-08-05T22:40:11.481451Z digest=sha256:4bfba485361722f4b5dba0c2c9e818a9e76f5c39a1ccf5b9b050f0c99ac4c585

Observation 8a827e8e-1826-430f-9724-b2e5f4f9b91f · outbound

This paper cites Weighted 3D volume reconstruction from series of slice data using a modified Allen – Cahn equation.

Variational volume reconstruction with the Deep Ritz Method Weighted 3D volume reconstruction from series of slice data using a modified Allen – Cahn equation

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.644630Z

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=arxiv_source observed=2026-08-05T22:40:11.600320Z digest=sha256:430daab6d344eb83a6aebe6619719bf08c23921fcba410e0f59c7213b97e227a

Observation ef9be59a-d8d7-476c-acf8-d60a6c2e6940 · outbound

This paper cites Multicomponent volume reconstruction from slice data using a modified multicomponent Cahn – Hilliard system.

Variational volume reconstruction with the Deep Ritz Method Multicomponent volume reconstruction from slice data using a modified multicomponent Cahn – Hilliard system

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.632283Z

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=arxiv_source observed=2026-08-05T22:40:11.745273Z digest=sha256:93c621946641b631e2699a82fc5e43ac4c18dd7de69138416490c8191a1c16d3

Observation 222aa050-2cbc-4d6f-8362-aa3591743cb5 · outbound

This paper cites Measuring three-dimensional tibiofemoral kinematics using dual-slice real-time magnetic resonance imaging.

Variational volume reconstruction with the Deep Ritz Method Measuring three-dimensional tibiofemoral kinematics using dual-slice real-time magnetic resonance imaging

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.620333Z

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=arxiv_source observed=2026-08-05T22:40:11.900866Z digest=sha256:2e27656fcef7a085da924bf42746e87c3c2357333fb2df60ef5db28905da6d28

Observation c92e896a-f828-4d7e-86bd-bc22df9f42e9 · outbound

This paper cites Higher-order multi-scale deep Ritz method for multi-scale problems of authentic composite materials, August 2023.

Variational volume reconstruction with the Deep Ritz Method Higher-order multi-scale deep Ritz method for multi-scale problems of authentic composite materials, August 2023

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.608330Z

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=arxiv_source observed=2026-08-05T22:40:12.009513Z digest=sha256:bb887f3d5494f350efb237b427506930ed260a31e2d533b784e17980c938cfc1

Observation ea7900fd-264e-410a-af6f-6021ee5fdfc4 · outbound

This paper cites Deep Ritz method with adaptive quadrature for linear elasticity.

Variational volume reconstruction with the Deep Ritz Method Deep Ritz method with adaptive quadrature for linear elasticity

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.595840Z

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 2744dacd-4495-4dd0-9211-2c857cea71fd · outbound

This paper cites Manav, R.

Variational volume reconstruction with the Deep Ritz Method Manav, R

Reference 36

Resolution
verified fuzzy
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source=arxiv_source observed=2026-08-05T22:40:12.262841Z digest=sha256:9576571c2b3a3ecf0d35df749e1f2c10cac6e5db19babf38b256d23ba96a1a3d

Observation 4e061e39-ed36-49f2-b573-fbaac6f84230 · outbound

This paper cites NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis.

Variational volume reconstruction with the Deep Ritz Method NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Reference 37

Resolution
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no resolver link, observed 2026-08-05T22:40:12.392720Z

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source=arxiv_source observed=2026-08-05T22:40:12.392720Z digest=sha256:b685d9cda0b84ff31bcb754937023eced2c10f73ce8031b0e3b0e888548aabf0

Observation 95fc97ea-895d-433c-83b0-955a948d504a · outbound

This paper cites Real time 3D reconstruction for enhanced cybersecurity of additive manufacturing processes.

Variational volume reconstruction with the Deep Ritz Method Real time 3D reconstruction for enhanced cybersecurity of additive manufacturing processes

Reference 38

Resolution
verified fuzzy
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source=arxiv_source observed=2026-08-05T22:40:12.477122Z digest=sha256:460338518bac9a5fd7359f927eb5d378b263a73ce31655b13ac43e3995422f86

Observation 40f67a16-c757-4c5b-8964-e92809a03457 · outbound

This paper cites Interpolating Implicit Surfaces From Scattered Surface Data Using Compactly Supported Radial Basis Functions.

Variational volume reconstruction with the Deep Ritz Method Interpolating Implicit Surfaces From Scattered Surface Data Using Compactly Supported Radial Basis Functions

Reference 39

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

source=arxiv_source observed=2026-08-05T22:40:12.606251Z digest=sha256:933d139d0aee28d4b681768a02a7e99a2e09012c7b34f756cb4253aa28c0b1f7

Observation ee9d4c52-8438-4bd5-acf2-4e9d72b96c40 · outbound

This paper cites Brain MRI super-resolution using deep 3D convolutional networks.

Variational volume reconstruction with the Deep Ritz Method Brain MRI super-resolution using deep 3D convolutional networks

Reference 40

Resolution
verified fuzzy
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source=arxiv_source observed=2026-08-05T22:40:12.712664Z digest=sha256:2b16ee9e080af04572915202dbd556b251af22a2aca55483e4843662f1766eac

Observation 330f32ad-01a4-40db-8006-58abad10dc20 · outbound

This paper cites A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction.

Variational volume reconstruction with the Deep Ritz Method A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction

Reference 41

Resolution
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local_arxiv, observed 2026-08-05T22:40:13.217618Z

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source=arxiv_source observed=2026-08-05T22:40:12.802119Z digest=sha256:fac827ffeeb140e6a6f0f5f6db5bb7824858d48a53a1d17eded0392208a2db11

Observation 51a62a8a-d5d1-4189-bda2-dcc93835e1aa · outbound

This paper cites Variational methods with application to medical image segmentation: A survey.

Variational volume reconstruction with the Deep Ritz Method Variational methods with application to medical image segmentation: A survey

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.530402Z

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source=arxiv_source observed=2026-08-05T22:40:12.901805Z digest=sha256:1a0bd033ce0dc847c1d96655e6a97060d831a0e724535766ac4ca20a9a9142cc

Observation c59561b8-3f23-4617-b73d-2620dee49d48 · outbound

This paper cites Variational Methods for Image Segmentation.

Variational volume reconstruction with the Deep Ritz Method Variational Methods for Image Segmentation

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.515482Z

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

source=arxiv_source observed=2026-08-05T22:40:12.953976Z digest=sha256:66897b085722da2b07447bd9f3c954ea2fe2918e1965a076863838bd64152bcf

Observation c41453ce-0b66-48ca-9b35-49b48ea6bd20 · outbound

This paper cites Sukumar and Ankit Srivastava.

Variational volume reconstruction with the Deep Ritz Method Sukumar and Ankit Srivastava

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.501143Z

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source=arxiv_source observed=2026-08-05T22:40:13.082796Z digest=sha256:d82aea6f7a0fd93dcad4a7edcfd560dde19cefb47d45fc51ff49a80f6b8e060e

Observation 9fd0d268-f888-40d9-9955-0eed4a43f9ec · outbound

This paper cites Deep variational network for rapid 4D flow MRI reconstruction.

Variational volume reconstruction with the Deep Ritz Method Deep variational network for rapid 4D flow MRI reconstruction

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:40:13.197274Z

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source=arxiv_source observed=2026-08-05T22:40:13.102649Z digest=sha256:6cc39d69688a8c3a02c5946c6fd85be2411c0859fb08eef8bfb53c803b888fa9

Observation c75c1127-00c2-4f6a-a5c9-e6887539673c · outbound

This paper cites Young, Yaël Balbastre, Bruce Fischl, Polina Golland, and Juan Eugenio Iglesias.

Variational volume reconstruction with the Deep Ritz Method Young, Yaël Balbastre, Bruce Fischl, Polina Golland, and Juan Eugenio Iglesias

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.485660Z

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=arxiv_source observed=2026-08-05T22:40:13.107384Z digest=sha256:c8782239cd083ac927f19e10e24b81359714ddda82c3b7f91f911ee224e68c69

Observation 79e52bef-9af7-4091-9918-b90fb2a5693c · outbound

This paper cites Super-Resolution Surface Reconstruction from Few Low-Resolution Slices.

Variational volume reconstruction with the Deep Ritz Method Super-Resolution Surface Reconstruction from Few Low-Resolution Slices

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:40:13.175797Z

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source=arxiv_source observed=2026-08-05T22:40:13.111344Z digest=sha256:b723c72b55f078744d6653d583ed5357f3fb35009b9fb2b4e92fd1ef5cc2cab0

Observation 46dc6429-e93e-49cb-9b70-c0f6f758bed8 · outbound

This paper cites Image Segmentation Using Euler ’s Elastica as the Regularization.

Variational volume reconstruction with the Deep Ritz Method Image Segmentation Using Euler ’s Elastica as the Regularization

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:40:13.470772Z

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source=arxiv_source observed=2026-08-05T22:40:13.115598Z digest=sha256:f3bf9301f2fda3dda1705a522c575a1216061ca650f95f25fe7a3c1367df94b9

Pith citing papers

Observation 243a5312-46df-40a5-b905-adaa0ff96276 · inbound

Learning Gradient Flow: Using Equation Discovery to Accelerate Engineering Optimization cites this paper.

Learning Gradient Flow: Using Equation Discovery to Accelerate Engineering Optimization Variational volume reconstruction with the Deep Ritz Method

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-02T23:34:48.867421Z

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source=pdf_text observed=2026-08-02T23:34:48.867421Z digest=sha256:0ef56f5b5348ed1411063f261076adac45ab8dac2fd5666b262638acbd4d6d08