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Paper Citation Record · LEDGER

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes

As of 9 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 2 inbound Pith citation observations for arXiv:2502.07145.

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

pith.paper-citation-record.v1
2502.07145 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

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measured 59 of 59 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T01:08:33.453029Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:11:01.065864Z

Reference resolution

57 of 57 outbound references displayed

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External citation measurements

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Outbound references

Observation 857558e0-8fe5-480e-996d-dc1754003929 · outbound

This paper cites Evaluation of normal morphology of mandibular condyle: a radiographic survey,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Evaluation of normal morphology of mandibular condyle: a radiographic survey,

Reference 1

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Observation d0ed773c-eb84-4683-aa8d-42c0bbfd2867 · outbound

This paper cites Statistical modeling of craniofacial shape and texture,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Statistical modeling of craniofacial shape and texture,

Reference 2

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Observation 84c760f3-e571-4ccd-a7ed-f61d0ad2d11d · outbound

This paper cites 3dcmm: 3d comprehensive morphable models with uv-unet for accurate head creation,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes 3dcmm: 3d comprehensive morphable models with uv-unet for accurate head creation,

Reference 3

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Observation a4e7dcce-12aa-4f0e-82fa-5ec1d5200c72 · outbound

This paper cites Statistical models and implant customization in hip arthroplasty: Seeking patient satisfaction through design,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Statistical models and implant customization in hip arthroplasty: Seeking patient satisfaction through design,

Reference 4

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Observation 9ebf2574-8afc-40ca-ade2-e504cdc9f668 · outbound

This paper cites Machine learning based liver disease diagnosis: A systematic review,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Machine learning based liver disease diagnosis: A systematic review,

Reference 5

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Observation 5c836a2d-5ccd-42cf-b34e-5b61163a10f6 · outbound

This paper cites A radiation-free classification pipeline for craniosynostosis using statistical shape modeling,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes A radiation-free classification pipeline for craniosynostosis using statistical shape modeling,

Reference 6

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Observation 89d88db9-62a1-48b4-a6b3-d407be674e54 · outbound

This paper cites Statistical shape model-based tibiofibular assessment of syndesmotic ankle lesions using weight- bearing ct,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Statistical shape model-based tibiofibular assessment of syndesmotic ankle lesions using weight- bearing ct,

Reference 7

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Observation 985f8594-1cf5-4106-8e40-b3ad5549d299 · outbound

This paper cites Feasibility of a longitudinal statistical atlas model to study aortic growth in congenital heart disease,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Feasibility of a longitudinal statistical atlas model to study aortic growth in congenital heart disease,

Reference 8

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Observation 60c7ef23-e8b4-4118-8bea-2e7178aefa1d · outbound

This paper cites Statistical shape analysis of the tricuspid valve in hypoplastic left heart syndrome,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Statistical shape analysis of the tricuspid valve in hypoplastic left heart syndrome,

Reference 9

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Observation 6e1fb6c5-f688-488d-9abe-5b299178f91c · outbound

This paper cites High variability of acetabular offset in primary hip osteoarthritis influences acetabular reaming—a computed tomography–based anatomic study,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes High variability of acetabular offset in primary hip osteoarthritis influences acetabular reaming—a computed tomography–based anatomic study,

Reference 10

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Observation 28389384-b2aa-494b-990a-407430a18507 · outbound

This paper cites Dynamic digital twin: Diagnosis, treatment, prediction, and prevention of disease during the life course,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Dynamic digital twin: Diagnosis, treatment, prediction, and prevention of disease during the life course,

Reference 11

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Observation abb110aa-00bf-4f88-9ec3-37020a252a8e · outbound

This paper cites Human digital twin for personalized healthcare: Vision, architecture and future directions,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Human digital twin for personalized healthcare: Vision, architecture and future directions,

Reference 12

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Observation 059b7a4b-e05d-4328-b568-832fda015df8 · outbound

This paper cites Morphometry of anatomical shape complexes with dense deformations and sparse parameters,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Morphometry of anatomical shape complexes with dense deformations and sparse parameters,

Reference 13

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Source-reported events for the cited work

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Observation 5a6122e0-2900-4cea-ac7a-d1e137b5a846 · outbound

This paper cites A level set model for image classification,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes A level set model for image classification,

Reference 14

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Observation 873f32f9-4e27-47fb-ad26-d07726c47403 · outbound

This paper cites Framework for the statistical shape analysis of brain structures using spharm-pdm,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Framework for the statistical shape analysis of brain structures using spharm-pdm,

Reference 15

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Observation e5f1ad13-983f-4a92-999b-5768caebb734 · outbound

This paper cites Statistical models of sets of curves and surfaces based on currents,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Statistical models of sets of curves and surfaces based on currents,

Reference 16

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Observation 751cde0e-fb14-4c61-bda8-f149bf2f4b0d · outbound

This paper cites Shape modeling and analysis with entropy-based particle systems,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Shape modeling and analysis with entropy-based particle systems,

Reference 17

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Observation bf3eedd4-dc3d-4be4-9f21-9a587a2ff6ad · outbound

This paper cites Particle-based shape analysis of multi-object complexes,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Particle-based shape analysis of multi-object complexes,

Reference 18

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Observation 580e00a1-b2b8-4d94-abd9-7963d91a06c7 · outbound

This paper cites Computational anatomy for multi-organ analysis in medical imaging: A review,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Computational anatomy for multi-organ analysis in medical imaging: A review,

Reference 19

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Observation 03295d66-9914-4815-81ff-6f72590366c0 · outbound

This paper cites Mesh2ssm: From surface meshes to statis- tical shape models of anatomy,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Mesh2ssm: From surface meshes to statis- tical shape models of anatomy,

Reference 20

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Source-reported events for the cited work

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Observation 04f691fe-b058-4f3b-b0b4-ec50b690785e · outbound

This paper cites Point2SSM: Learning Morphological Variations of Anatomies from Point Cloud.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Point2SSM: Learning Morphological Variations of Anatomies from Point Cloud

Reference 21

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Observation 444af339-e80d-4b1c-bdd3-8dd7d2f2c68f · outbound

This paper cites Landmark-free statistical shape modeling via neural flow deformations,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Landmark-free statistical shape modeling via neural flow deformations,

Reference 22

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Observation 1f21c3c6-1e48-4910-918a-c0458327792c · outbound

This paper cites Deepssm: A blueprint for image-to-shape deep learning models,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Deepssm: A blueprint for image-to-shape deep learning models,

Reference 23

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Observation 5162fe66-cdc7-44c3-a5b5-763dde9205cf · outbound

This paper cites Deepssm: a deep learning framework for statistical shape modeling from raw im- ages,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Deepssm: a deep learning framework for statistical shape modeling from raw im- ages,

Reference 24

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Observation 6cce819b-1627-4280-b2ac-90622191959a · outbound

This paper cites A universal and flexible framework for unsupervised statistical shape model learning,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes A universal and flexible framework for unsupervised statistical shape model learning,

Reference 25

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Observation ce7b1b04-6d4f-4abc-87f3-99b1c8336964 · outbound

This paper cites An End-to-End Deep Learning Generative Framework for Refinable Shape Matching and Generation.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes An End-to-End Deep Learning Generative Framework for Refinable Shape Matching and Generation

Reference 26

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Observation e66ec5e7-2e65-49a6-a9ae-774aaecc71b3 · outbound

This paper cites An introduction to variational autoencoders,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes An introduction to variational autoencoders,

Reference 27

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Observation e1e87980-c96d-46e6-a756-7a684bf94b4e · outbound

This paper cites Variational inference with normalizing flows,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Variational inference with normalizing flows,

Reference 28

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This paper cites Density estimation using Real NVP.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Density estimation using Real NVP

Reference 29

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This paper cites Build- ing and testing a statistical shape model of the human ear canal,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Build- ing and testing a statistical shape model of the human ear canal,

Reference 30

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Observation c150eb36-eb6a-4f0d-b9f4-76047e1d25c3 · outbound

This paper cites Statistical shape model generation using nonrigid deformation of a template mesh,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Statistical shape model generation using nonrigid deformation of a template mesh,

Reference 31

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Observation 39c1cb0b-393d-4dff-9ef0-93b689ecfe13 · outbound

This paper cites Deformable models in medical image analysis,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Deformable models in medical image analysis,

Reference 32

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Observation 9b8dac08-2176-4ccf-ada8-ab7da5e86d25 · outbound

This paper cites Shapeworks: Particle-based shape correspondence and visualization software,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Shapeworks: Particle-based shape correspondence and visualization software,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:05.034779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.460218Z digest=sha256:5719907ffa91e3f01a5e6f99d436d72bf2cbb5759eac1de578954f3e8850f99e

Observation 9920de4b-7ec6-4b6e-87d7-064e2e1ad3e2 · outbound

This paper cites Entropy-based particle correspondence for shape populations,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Entropy-based particle correspondence for shape populations,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-08T13:44:04.465074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:44:04.465074Z digest=sha256:73effb28af52a8fe2c0e7238d49d9fe11d8cbba7ee8f3977c19609d06b29eedd

Observation f7f3ce62-fdba-4424-be43-927fd31b0086 · outbound

This paper cites From images to probabilistic anatomical shapes: A deep variational bottleneck approach,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes From images to probabilistic anatomical shapes: A deep variational bottleneck approach,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:05.008298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.469891Z digest=sha256:cbd0af60167e57d5e1a06b879f0eec2da7f4cdca995e7faca713b6069b281bc0

Observation e47462a5-8f51-4be4-9f51-6e6e406132cd · outbound

This paper cites Dpc: Unsupervised deep point correspondence via cross and self construction,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Dpc: Unsupervised deep point correspondence via cross and self construction,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.991892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.474937Z digest=sha256:8b8614a47f7b4a1edb6cbdfddd54ce22d8168250ddd54f6a72ac14bd062047db

Observation c093735a-e4fa-42cb-b0ed-ae1908d75abf · outbound

This paper cites Dynamic graph cnn for learning on point clouds,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Dynamic graph cnn for learning on point clouds,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-08T13:44:04.480622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:44:04.480622Z digest=sha256:7098a646d9e58074643e688ce230cf9b8fba3543326503220aaff8ca0461baca

Observation 323ec78d-0a53-4707-a464-26aeb05b844a · outbound

This paper cites Unsupervised learning of intrinsic structural representation points,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Unsupervised learning of intrinsic structural representation points,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.966281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.485180Z digest=sha256:5f06f5b9980baa46e64a900b9bda0cf729be589afd7f2e174ac335b003bfebeb

Observation d7a7909b-afa5-421e-87a3-dd332b171b1a · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes ShapeNet: An Information-Rich 3D Model Repository

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-08T13:44:04.489833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:44:04.489833Z digest=sha256:edaf685fbb4701afddf5f9e8f6d571b474b983dd42d7cf58069e4bb639d9e124

Observation 20bd3ec8-4d1a-4144-b3b7-9f5cce804f9a · outbound

This paper cites 3d-r2n2: A unified approach for single and multi-view 3d object reconstruction,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes 3d-r2n2: A unified approach for single and multi-view 3d object reconstruction,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.951164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.495190Z digest=sha256:01e07e436c5c8e5ce4d72cc9411a6cb16dca559cda58e54769b5780798c5b805

Observation 3d15593a-2376-4214-b1ae-c33aa93f6add · outbound

This paper cites Graph convolutional networks: a comprehensive review,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Graph convolutional networks: a comprehensive review,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T13:44:04.500080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:44:04.500080Z digest=sha256:a1ff1281e10e51673f470d44531d22549cdc92d270df1dc6db140682a22d729f

Observation 5d9154e7-bf2e-48a6-b554-28b3c1f574f3 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Semi-Supervised Classification with Graph Convolutional Networks

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-08T13:44:04.504633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:44:04.504633Z digest=sha256:ab557c867a395ecb83f5b70fd6afefca218198d0499b56c6bf35bb62eaead4f6

Observation b1439c1e-e6d4-4775-9482-3a331cae14e8 · outbound

This paper cites Meshcnn: a network with an edge,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Meshcnn: a network with an edge,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-08T13:44:04.509671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:44:04.509671Z digest=sha256:6ee8615adc60a4eeacd57deebccf1950dc33391aa0dcebbbd67a06a5bec19f46

Observation 2206d487-cf50-4bc8-b5c3-1b8b1570351a · outbound

This paper cites Convolutional neural networks on graphs with fast localized spectral filtering,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Convolutional neural networks on graphs with fast localized spectral filtering,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.915489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.514318Z digest=sha256:6db871144558ee7277553fc60cdeeeecb2322802eae755774f95d2d9d3bf4bfa

Observation f30f6748-3e40-4101-b9da-445dcb606d5b · outbound

This paper cites Shapeflow: Learnable deformation flows among 3d shapes,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Shapeflow: Learnable deformation flows among 3d shapes,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.900661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.519911Z digest=sha256:b45ce7804e1f83392b075183138e748c7e1134a90a2863ecd5ed79ef3e92b6a8

Observation 57fd81d3-706e-49ca-a1d4-890362d0cff8 · outbound

This paper cites Im-net: Learning implicit fields for generative shape model- ing,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Im-net: Learning implicit fields for generative shape model- ing,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.884749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.524641Z digest=sha256:30f550964353bfbb4cd9a1e2694d73c6ac383b70f4e54dd2a3a32fda207d9260

Observation ac4d9784-1bd9-4fd8-adc1-7e3bee4e71bc · outbound

This paper cites Fixing a broken elbo,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Fixing a broken elbo,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.869234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.529399Z digest=sha256:bcec80a79616e6d5708ae9765ec33b6e434bc86ed2a6877b3ebe340b7baef4e8

Observation 11ac7ba8-25d8-4682-ab87-08bb32f90cf7 · outbound

This paper cites Learning continuous normalizing flows for faster convergence to target distribution via ascent regularizations,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Learning continuous normalizing flows for faster convergence to target distribution via ascent regularizations,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.853464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.533858Z digest=sha256:b3e4b07e71257c39725f40d32e4ea54f754d343d3cc93b924e83a9e35fd69fc8

Observation fd5c15c8-08e0-4946-bd5e-924afda5ab1b · outbound

This paper cites dpvaes: Fixing sample generation for regularized vaes,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes dpvaes: Fixing sample generation for regularized vaes,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.837933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.538687Z digest=sha256:dbdef2d983d928287c089d0fe12317a6c69a44e2a9c3ed6b6544b669a7ff7ad3

Observation e812ec21-e6ea-4438-9a3b-d32f9f658074 · outbound

This paper cites A large annotated medical image dataset for the development and evaluation of segmentation algorithms.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes A large annotated medical image dataset for the development and evaluation of segmentation algorithms

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T13:44:04.543663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:44:04.543663Z digest=sha256:fda27c94641c0a34f8bce94249ebb687b387a4e0cd810c366b6d4d2f457e41e5

Observation e868410a-d120-47f4-9b87-852d25495512 · outbound

This paper cites Abdomenct-1k: Is abdominal organ segmentation a solved problem?.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Abdomenct-1k: Is abdominal organ segmentation a solved problem?

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.821731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.548803Z digest=sha256:e201db9453d30c4b480e849f9f976f04cb8090e2eb08799b2a6155baf7eb6394

Observation a727f666-a4f2-4a05-9a83-d0634c1b2df7 · outbound

This paper cites Unsupervised shape correspondence estimation for anatomi- cal shapes,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Unsupervised shape correspondence estimation for anatomi- cal shapes,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.803952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.553544Z digest=sha256:e0d325a41de4428c9982fcf472371b22778ecab182a3762bd94a038b61469ecc

Observation a3d72b59-ba2a-4082-8ed5-1717fdb03112 · outbound

This paper cites Structural and functional remodeling of the left atrium: clinical and therapeutic im- plications for atrial fibrillation,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Structural and functional remodeling of the left atrium: clinical and therapeutic im- plications for atrial fibrillation,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.786903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.558513Z digest=sha256:15c66074a37353ddeb55b0980c8a1c239ff66e9262c0ab94bd722079591dc0c1

Observation f82a05ec-d329-4099-8dc1-40f0c6c7f7a3 · outbound

This paper cites Liver cirrhosis: relationship between fibrosis-associated hepatic morphological changes and portal hemo- dynamics using four-dimensional flow magnetic resonance imaging,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Liver cirrhosis: relationship between fibrosis-associated hepatic morphological changes and portal hemo- dynamics using four-dimensional flow magnetic resonance imaging,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.771101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.563008Z digest=sha256:c2c433b661861f9d1e4fb3bcdb7a55d8c8762aeecbb34d1b60b2d1e9dba67120

Observation 0ef9ecc3-5d25-4a2d-b0d1-fb3c1285497d · outbound

This paper cites Verse: a vertebrae labelling and segmentation benchmark for multi-detector ct images,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Verse: a vertebrae labelling and segmentation benchmark for multi-detector ct images,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.755046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.567817Z digest=sha256:0e9f77d03cd576f4de7913f832b10025728d73a883e0834b28d743cbc5b8c2bd

Observation 4cac24ed-e6b0-4ff0-bff4-d7b22d501960 · outbound

This paper cites Diffcd: A symmetric differentiable chamfer distance for neural implicit surface fitting.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Diffcd: A symmetric differentiable chamfer distance for neural implicit surface fitting

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.738368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.572323Z digest=sha256:ef7cbc670ed6c0ca5f67e61f3637fc02d432c69c4bc778657a385e0e4736eda5

Observation a08de07c-605d-4a20-a3cb-e2bf39cc4518 · outbound

This paper cites Neural-imls: Self-supervised implicit moving least-squares network for surface reconstruction,.

Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Neural-imls: Self-supervised implicit moving least-squares network for surface reconstruction,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:44:04.721249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T13:44:04.577146Z digest=sha256:342f530362bc2ecf1d875749d801c79bbd5f8338ea8d9a98561e320d3b17379e

Pith citing papers

Observation 2cd8e367-a961-46e0-9557-bef621bc2f75 · inbound

MorphoFlow: Sparse-Supervised Generative Shape Modeling with Adaptive Latent Relevance cites this paper.

MorphoFlow: Sparse-Supervised Generative Shape Modeling with Adaptive Latent Relevance Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:11:01.072202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T15:08:43.292190Z digest=sha256:758e6658006ac828eebadc6fc4e5817ae18a22a8f791e9aefe83133342288eff

Observation efc67ea5-1774-4a89-bc63-e61c772b2790 · inbound

SCALP: Semi-Supervised Statistical Shape Modeling from Imperfect 3D Photogrammetry via Landmark-Anchored Spectral Warp cites this paper.

SCALP: Semi-Supervised Statistical Shape Modeling from Imperfect 3D Photogrammetry via Landmark-Anchored Spectral Warp Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-04T01:08:33.453029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T01:08:33.453029Z digest=sha256:6aa539bd43468fdc15954b670077d0c4e6b7c1ae1b75b7a9d6a21d971b6c9999