Paper Citation Record · LEDGER

Invariant Shape Representation Learning For Image Classification

As of 23 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 3 inbound Pith citation observations for arXiv:2411.12201.

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

pith.paper-citation-record.v1
2411.12201 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

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measured 72 of 72 standing notices

One-hop event checks from named stored sources.

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measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:06:10.960172Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T08:26:04.832138Z

Reference resolution

69 of 69 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4bc60424-03d0-4022-82ab-0ab4419e0f01 · outbound

This paper cites Invariant risk minimization games.

Invariant Shape Representation Learning For Image Classification Invariant risk minimization games

Reference 1

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Observation 26c8f2b3-f453-45cd-b8ae-2613ef7d837c · outbound

This paper cites Invariant Risk Minimization.

Invariant Shape Representation Learning For Image Classification Invariant Risk Minimization

Reference 2

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Observation 2fa30a22-5e89-4536-9f97-4b49b4736322 · outbound

This paper cites Vivit: A video vision transformer.

Invariant Shape Representation Learning For Image Classification Vivit: A video vision transformer

Reference 3

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Observation dbf260c7-bfaf-43c3-bdad-ca3a67a1a2ec · outbound

This paper cites Sur la g ´eom´etrie diff ´erentielle des groupes de lie de dimension infinie et ses applications `a l’hydrodynamique des fluides parfaits.

Invariant Shape Representation Learning For Image Classification Sur la g ´eom´etrie diff ´erentielle des groupes de lie de dimension infinie et ses applications `a l’hydrodynamique des fluides parfaits

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.992815Z

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Observation 0be351e8-e622-411e-9dd7-c824516e604e · outbound

This paper cites Computing large deformation metric map- pings via geodesic flows of diffeomorphisms.

Invariant Shape Representation Learning For Image Classification Computing large deformation metric map- pings via geodesic flows of diffeomorphisms

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.971776Z

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Observation 6df11cd8-6aaa-4b0c-8176-b5e5f6b05ed2 · outbound

This paper cites Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomor- phisms.

Invariant Shape Representation Learning For Image Classification Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomor- phisms

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.958908Z

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Observation 4f35cbbe-e1eb-4329-9452-5861e715114d · outbound

This paper cites Parametriza- tion of closed surfaces for 3-d shape description.

Invariant Shape Representation Learning For Image Classification Parametriza- tion of closed surfaces for 3-d shape description

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.943937Z

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Observation 2aaf94c5-1e02-45a7-a370-3d526beca8fc · outbound

This paper cites Causal- ity matters in medical imaging.

Invariant Shape Representation Learning For Image Classification Causal- ity matters in medical imaging

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.834659Z

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Observation 34052da9-428b-4d86-81e3-ebfc6e6218b2 · outbound

This paper cites Semi-supervised task-driven data augmentation for medical image segmentation.

Invariant Shape Representation Learning For Image Classification Semi-supervised task-driven data augmentation for medical image segmentation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.676510Z

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Observation f7e4095a-9d0e-4305-8ac0-6efed3143fd1 · outbound

This paper cites In- variant rationalization.

Invariant Shape Representation Learning For Image Classification In- variant rationalization

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.597675Z

Source-reported events for the cited work

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Observation 1c492376-1a1c-4cfc-b028-db6c46981141 · outbound

This paper cites Enhancing mr image segmentation with re- alistic adversarial data augmentation.

Invariant Shape Representation Learning For Image Classification Enhancing mr image segmentation with re- alistic adversarial data augmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.584276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 07f69767-8eff-439e-9842-ba4993594cad · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

Invariant Shape Representation Learning For Image Classification TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 12

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Observation fde15239-f5e4-4ae2-b18c-e2fe37a005ae · outbound

This paper cites Active shape models-their training and application.

Invariant Shape Representation Learning For Image Classification Active shape models-their training and application

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.560241Z

Source-reported events for the cited work

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Observation 30728863-1eeb-400b-ae63-739b1927a20d · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Invariant Shape Representation Learning For Image Classification An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 14

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Observation 4f1a671a-5c5c-4a6f-924c-5d946af4cf63 · outbound

This paper cites Domain-adversarial training of neural networks.

Invariant Shape Representation Learning For Image Classification Domain-adversarial training of neural networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.456017Z

Source-reported events for the cited work

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Observation d908816c-d4bd-4ab3-b9ec-59cfe8f1bc52 · outbound

This paper cites ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness.

Invariant Shape Representation Learning For Image Classification ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Reference 16

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Source-reported events for the cited work

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Observation de98c92f-4e9c-4272-95d1-b5a0fc333b0a · outbound

This paper cites Confidence calibration for domain generalization under covariate shift.

Invariant Shape Representation Learning For Image Classification Confidence calibration for domain generalization under covariate shift

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.346619Z

Source-reported events for the cited work

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Observation b0a74890-1975-430b-b8fd-9c5c910759e0 · outbound

This paper cites Deep residual learning for image recognition.

Invariant Shape Representation Learning For Image Classification Deep residual learning for image recognition

Reference 18

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Source-reported events for the cited work

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Observation 5f84478c-0705-49e8-ad84-d27c1e603952 · outbound

This paper cites Diffeo- morphic autoencoders for lddmm atlas building.

Invariant Shape Representation Learning For Image Classification Diffeo- morphic autoencoders for lddmm atlas building

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T17:53:30.006975Z

Source-reported events for the cited work

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Observation 515a5138-7639-4efa-95de-1bb6dae4d004 · outbound

This paper cites Fast geodesic regression for population-based image analysis.

Invariant Shape Representation Learning For Image Classification Fast geodesic regression for population-based image analysis

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.254252Z

Source-reported events for the cited work

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Observation 501051ef-1b68-484f-ab36-34f90e581c2d · outbound

This paper cites Brain tumor detection using convolutional neural net- work.

Invariant Shape Representation Learning For Image Classification Brain tumor detection using convolutional neural net- work

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.128003Z

Source-reported events for the cited work

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Observation a088cd75-717e-4bc6-b26e-71596838d9ef · outbound

This paper cites MGAug: Multimodal Geometric Augmentation in Latent Spaces of Image Deformations.

Invariant Shape Representation Learning For Image Classification MGAug: Multimodal Geometric Augmentation in Latent Spaces of Image Deformations

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-12T17:53:32.339133Z

Source-reported events for the cited work

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Observation cd5d2d16-29a5-4636-823f-ba29265b8a90 · outbound

This paper cites The alzheimer’s disease neuroimaging initiative (adni): Mri methods.

Invariant Shape Representation Learning For Image Classification The alzheimer’s disease neuroimaging initiative (adni): Mri methods

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.053530Z

Source-reported events for the cited work

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Observation 3147d876-6ad7-41c1-8319-ad665e776ab0 · outbound

This paper cites Sadir: shape-aware diffusion models for 3d image recon- struction.

Invariant Shape Representation Learning For Image Classification Sadir: shape-aware diffusion models for 3d image recon- struction

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.041308Z

Source-reported events for the cited work

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Observation d95d23cd-259d-447f-ba79-d4d1073df999 · outbound

This paper cites The quick, draw!-ai experi- ment.

Invariant Shape Representation Learning For Image Classification The quick, draw!-ai experi- ment

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:35.027822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 78fc6be0-ad4a-4abb-9f41-bd08b36cb25e · outbound

This paper cites Improved image registration by sparse patch-based deformation estimation.

Invariant Shape Representation Learning For Image Classification Improved image registration by sparse patch-based deformation estimation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.873203Z

Source-reported events for the cited work

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Observation f2f22f79-7ebf-4d8d-a012-d33dba6ff37a · outbound

This paper cites Arrhythmias and mortality in conges- tive heart failure.

Invariant Shape Representation Learning For Image Classification Arrhythmias and mortality in conges- tive heart failure

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.780268Z

Source-reported events for the cited work

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Observation 223592be-6e13-43d6-8e3a-e71f4447543f · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

Invariant Shape Representation Learning For Image Classification Imagenet classification with deep convolutional neural net- works

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.766548Z

Source-reported events for the cited work

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Observation 9ae04779-61a9-49e6-bc40-8ecfc2ae9bc5 · outbound

This paper cites A simple feature augmentation for do- main generalization.

Invariant Shape Representation Learning For Image Classification A simple feature augmentation for do- main generalization

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.740046Z

Source-reported events for the cited work

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Observation 23aefc48-3b23-4c02-9dfc-7c7401dc8889 · outbound

This paper cites Bayesian invariant risk minimization.

Invariant Shape Representation Learning For Image Classification Bayesian invariant risk minimization

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.635295Z

Source-reported events for the cited work

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Observation a395d373-1ea1-4a0d-aa5c-d07d4d69072a · outbound

This paper cites Federated semi-supervised medical image classifica- tion via inter-client relation matching.

Invariant Shape Representation Learning For Image Classification Federated semi-supervised medical image classifica- tion via inter-client relation matching

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.552898Z

Source-reported events for the cited work

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Observation 25f80f2a-a25d-42cb-b810-2632d67a94ba · outbound

This paper cites Un- biased atlas formation via large deformations metric map- ping.

Invariant Shape Representation Learning For Image Classification Un- biased atlas formation via large deformations metric map- ping

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.541797Z

Source-reported events for the cited work

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Observation 1e79c8f6-4081-4cfb-a504-bd33fa828d3e · outbound

This paper cites Invariant causal representation learning for out-of-distribution generalization.

Invariant Shape Representation Learning For Image Classification Invariant causal representation learning for out-of-distribution generalization

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.522140Z

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Observation 32ffea45-7cb5-4b77-a766-95c2331d1ad1 · outbound

This paper cites Geodesic shooting for computational anatomy.

Invariant Shape Representation Learning For Image Classification Geodesic shooting for computational anatomy

Reference 34

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Source-reported events for the cited work

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Observation ede27041-e15a-4d21-8120-21b6b7fce061 · outbound

This paper cites Representation Learning via Invariant Causal Mechanisms.

Invariant Shape Representation Learning For Image Classification Representation Learning via Invariant Causal Mechanisms

Reference 35

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Source-reported events for the cited work

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Observation a3e25f1c-70b3-430c-8b03-332a6757c9c7 · outbound

This paper cites Learning from failure: De-biasing classifier from biased classifier.

Invariant Shape Representation Learning For Image Classification Learning from failure: De-biasing classifier from biased classifier

Reference 36

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Observation 91c05b5a-8541-40ce-9e1e-3d54731fc155 · outbound

This paper cites Numerical optimiza- tion.

Invariant Shape Representation Learning For Image Classification Numerical optimiza- tion

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0abdae7-ead1-4515-8742-41ac26e46094 · outbound

This paper cites Segmentation, registration, and measurement of shape variation via im- age object shape.

Invariant Shape Representation Learning For Image Classification Segmentation, registration, and measurement of shape variation via im- age object shape

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.390316Z

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Observation f89323bf-0b97-45da-8fdd-e51389cc8068 · outbound

This paper cites Ventricular arrhythmia in congestive heart failure.

Invariant Shape Representation Learning For Image Classification Ventricular arrhythmia in congestive heart failure

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.377387Z

Source-reported events for the cited work

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Observation 8c85cd66-f13e-4840-a56e-e90cfa4bb4ee · outbound

This paper cites Age, alzheimer disease, and brain structure.Neu- rology, 73(22):1899–1905, 2009.

Invariant Shape Representation Learning For Image Classification Age, alzheimer disease, and brain structure.Neu- rology, 73(22):1899–1905, 2009

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.350005Z

Source-reported events for the cited work

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Observation abe95fbc-9a7a-48f7-baf4-76b32490acda · outbound

This paper cites Deep structural causal shape models.

Invariant Shape Representation Learning For Image Classification Deep structural causal shape models

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.284459Z

Source-reported events for the cited work

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Observation a729b9a1-ed0d-4890-96a2-e2229104c015 · outbound

This paper cites Deformable Image Registration for Surgical Guidance using Intraoperative Cone-Beam CT.

Invariant Shape Representation Learning For Image Classification Deformable Image Registration for Surgical Guidance using Intraoperative Cone-Beam CT

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.144265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 37ae8b2d-ad78-489a-97d5-9252bd7d9373 · outbound

This paper cites Within-subject template estimation for unbi- ased longitudinal image analysis.

Invariant Shape Representation Learning For Image Classification Within-subject template estimation for unbi- ased longitudinal image analysis

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.111274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1c779c21-9022-4580-bcc9-cd3cd23e7853 · outbound

This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

Invariant Shape Representation Learning For Image Classification U- net: Convolutional networks for biomedical image segmen- tation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T17:53:31.152510Z

Source-reported events for the cited work

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Observation b3ce0d4f-8bd2-4e0a-97c2-524c11bd1022 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Invariant Shape Representation Learning For Image Classification Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-12T17:53:31.203354Z

Source-reported events for the cited work

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Observation ba877185-d024-4160-aca8-3dbb9d756c14 · outbound

This paper cites Return of frus- tratingly easy domain adaptation.

Invariant Shape Representation Learning For Image Classification Return of frus- tratingly easy domain adaptation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:34.057225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2575fb91-a5f8-4591-a3f5-36e7c6e4286b · outbound

This paper cites Deep coral: Correlation alignment for deep domain adaptation.

Invariant Shape Representation Learning For Image Classification Deep coral: Correlation alignment for deep domain adaptation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.947944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0e405910-cafb-4377-95c7-2baa38e611e5 · outbound

This paper cites Domain adaptation with conditional dis- tribution matching and generalized label shift.

Invariant Shape Representation Learning For Image Classification Domain adaptation with conditional dis- tribution matching and generalized label shift

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.855200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bfbb082c-975f-43a5-bf7e-0f8c93fdb220 · outbound

This paper cites Causality-aware con- volutional neural networks for advanced image classification and generation.

Invariant Shape Representation Learning For Image Classification Causality-aware con- volutional neural networks for advanced image classification and generation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.772726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d8d58af4-3284-4ea3-81b2-acf6efe6308e · outbound

This paper cites Statistics on diffeomorphisms via tangent space rep- resentations.

Invariant Shape Representation Learning For Image Classification Statistics on diffeomorphisms via tangent space rep- resentations

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.688565Z

Source-reported events for the cited work

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Observation df9d1870-9d40-4ae2-96aa-f0a1d141a7a4 · outbound

This paper cites Principles of risk minimization for learn- ing theory.

Invariant Shape Representation Learning For Image Classification Principles of risk minimization for learn- ing theory

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.593356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 64e3c47a-83fb-44c8-80b7-433e4b8e4a16 · outbound

This paper cites Diffeomorphic 3d image registration via geodesic shooting using an efficient adjoint calculation.

Invariant Shape Representation Learning For Image Classification Diffeomorphic 3d image registration via geodesic shooting using an efficient adjoint calculation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.522312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 508cf90e-5011-4c3b-ae41-722224b289d8 · outbound

This paper cites Detect and correct bias in multi-site neuroimaging datasets.Medical Image Analysis, 67:101879, 2021.

Invariant Shape Representation Learning For Image Classification Detect and correct bias in multi-site neuroimaging datasets.Medical Image Analysis, 67:101879, 2021

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.455602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 70cf653d-3660-447a-8cd8-2b8fe1c1e015 · outbound

This paper cites On calibration and out-of-domain generalization.

Invariant Shape Representation Learning For Image Classification On calibration and out-of-domain generalization

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.368958Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d8e35364-9bf7-4b64-b947-a8b448c4aaf0 · outbound

This paper cites Geo-sic: Learning de- formable geometric shapes in deep image classifiers.

Invariant Shape Representation Learning For Image Classification Geo-sic: Learning de- formable geometric shapes in deep image classifiers

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.330953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1d8c436e-b028-4990-9ebd-183232cd84c8 · outbound

This paper cites Out-of-distribution generalization with causal invari- ant transformations.

Invariant Shape Representation Learning For Image Classification Out-of-distribution generalization with causal invari- ant transformations

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.248872Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 88333306-4bb7-48b1-8dac-da91d3d4a80b · outbound

This paper cites Ai based cmr assessment of biventricular function: clinical sig- nificance of intervendor variability and measurement errors.

Invariant Shape Representation Learning For Image Classification Ai based cmr assessment of biventricular function: clinical sig- nificance of intervendor variability and measurement errors

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.171103Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ab51f673-624c-4be9-9e99-d9a00531d409 · outbound

This paper cites Convolutional neural networks for classifica- tion of alzheimer’s disease: Overview and reproducible eval- uation.

Invariant Shape Representation Learning For Image Classification Convolutional neural networks for classifica- tion of alzheimer’s disease: Overview and reproducible eval- uation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.102368Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d500c9c6-28b7-46b7-baaa-b7fce7ad7114 · outbound

This paper cites Treatment learning causal transformer for noisy image classification.

Invariant Shape Representation Learning For Image Classification Treatment learning causal transformer for noisy image classification

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:33.034988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0ce89c53-44a1-480b-ac9e-f02f4155b0d5 · outbound

This paper cites Adversarial teacher-student representa- tion learning for domain generalization.

Invariant Shape Representation Learning For Image Classification Adversarial teacher-student representa- tion learning for domain generalization

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.967311Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 88f09dc7-160d-4713-bfc4-1b43996d4874 · outbound

This paper cites Improving out-of-distribution robustness via selective augmentation.

Invariant Shape Representation Learning For Image Classification Improving out-of-distribution robustness via selective augmentation

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T17:53:31.963629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e19b8311-8959-4828-b1f5-025c82e9b101 · outbound

This paper cites Atlas pre-selection strategies to enhance the efficiency and accuracy of multi-atlas brain seg- mentation tools.

Invariant Shape Representation Learning For Image Classification Atlas pre-selection strategies to enhance the efficiency and accuracy of multi-atlas brain seg- mentation tools

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.911633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9a01d663-80ef-4973-8470-3f1fa226f62c · outbound

This paper cites Interventional few-shot learning.

Invariant Shape Representation Learning For Image Classification Interventional few-shot learning

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.873278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cd83f812-4d55-4bca-8ae8-275bc3049ef3 · outbound

This paper cites Removal of con- founders via invariant risk minimization for medical diag- nosis.

Invariant Shape Representation Learning For Image Classification Removal of con- founders via invariant risk minimization for medical diag- nosis

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.812009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e61e9d11-e2a9-4001-a08e-6196017288d0 · outbound

This paper cites Visualizing and un- derstanding convolutional networks.

Invariant Shape Representation Learning For Image Classification Visualizing and un- derstanding convolutional networks

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.742106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c4263b33-5352-4a7c-a908-91d05c858031 · outbound

This paper cites Causal intervention for weakly- supervised semantic segmentation.

Invariant Shape Representation Learning For Image Classification Causal intervention for weakly- supervised semantic segmentation

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.695235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b0ce3a38-06cd-4934-b6ef-503b705d730f · outbound

This paper cites Statistical shape anal- ysis: From landmarks to diffeomorphisms, 2016.

Invariant Shape Representation Learning For Image Classification Statistical shape anal- ysis: From landmarks to diffeomorphisms, 2016

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.645587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 75c81309-6681-4ccd-be13-6cca8657cdc3 · outbound

This paper cites Training confounder-free deep learning models for medical applica- tions.

Invariant Shape Representation Learning For Image Classification Training confounder-free deep learning models for medical applica- tions

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.579324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f2560e55-fef1-4c79-9023-4ad3d591c059 · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmentation.

Invariant Shape Representation Learning For Image Classification Unet++: A nested u-net architecture for medical image segmentation

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:53:32.485006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation cbe77ea8-c2ab-46f7-af16-6584a842e5fd · inbound

ShapeEmbed: a self-supervised learning framework for 2D contour quantification cites this paper.

ShapeEmbed: a self-supervised learning framework for 2D contour quantification Invariant Shape Representation Learning For Image Classification

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T21:06:10.960172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fad4f7c-b476-479f-8699-3f1c8b6a1a86 · inbound

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification cites this paper.

Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification Invariant Shape Representation Learning For Image Classification

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T08:26:04.834417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5e0384a2-0e9a-49a7-93c6-6819fa555bc7 · inbound

Learning To Focus: Anatomy-Guided Attention Regularization for Medical Image Classification cites this paper.

Learning To Focus: Anatomy-Guided Attention Regularization for Medical Image Classification Invariant Shape Representation Learning For Image Classification

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T08:48:05.634202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.