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Paper Citation Record · LEDGER

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies

As of 11 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2502.01335.

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

pith.paper-citation-record.v1
2502.01335 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:44:34.983549Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

49 of 49 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a7381f86-ee32-424e-94c1-0678416fd70d · outbound

This paper cites 3d self-supervised methods for medical imaging.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies 3d self-supervised methods for medical imaging

Reference 1

Resolution
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Observation 6d26a4ea-1b86-47f1-937e-71f666c26198 · outbound

This paper cites Big self-supervised models advance medical image classification.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Big self-supervised models advance medical image classification

Reference 2

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Observation 18c01dc3-a718-4b75-aea0-c6bb93ac55ca · outbound

This paper cites Systematic comparison of semi-supervised and self-supervised learning for medical image classification.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Systematic comparison of semi-supervised and self-supervised learning for medical image classification

Reference 3

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Observation c7e10937-d731-4054-9432-aa95bfaf68f9 · outbound

This paper cites A Cookbook of Self-Supervised Learning.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies A Cookbook of Self-Supervised Learning

Reference 4

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Observation 02b56b73-1030-4832-be0b-481775cd3a14 · outbound

This paper cites The ssl interplay: Augmentations, inductive bias, and generalization.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies The ssl interplay: Augmentations, inductive bias, and generalization

Reference 5

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Observation 4f3a6ebd-3fc3-4b01-b5f1-17d54e0189dd · outbound

This paper cites V oco: A simple-yet-effective volume contrastive learning framework for 3d medical image analysis.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies V oco: A simple-yet-effective volume contrastive learning framework for 3d medical image analysis

Reference 6

Resolution
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Observation ad927b97-40c6-4091-98ae-fa10a0b6f09b · outbound

This paper cites Data2vec: A general framework for self-supervised learning in speech, vision and language.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Data2vec: A general framework for self-supervised learning in speech, vision and language

Reference 7

Resolution
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Source-reported events for the cited work

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Observation ca7dad45-f42b-4457-98c2-1e29314be2d9 · outbound

This paper cites Swinmm: Masked multi-view with swin transformers for 3d medical image segmentation.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Swinmm: Masked multi-view with swin transformers for 3d medical image segmentation

Reference 8

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Observation a0308d1b-b1de-4c20-b1a7-e42c4e58e4bd · outbound

This paper cites Benchmarking Supervised and Self-Supervised Learning Methods in A Large Ultrasound Multi-task Images Dataset.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Benchmarking Supervised and Self-Supervised Learning Methods in A Large Ultrasound Multi-task Images Dataset

Reference 9

Resolution
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Observation fd87456f-d096-4454-adca-18744ff3772b · outbound

This paper cites Efficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Efficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning

Reference 10

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Observation 884007f9-d58e-401d-84e1-9ee81e0a1da7 · outbound

This paper cites InsCLR: Improving Instance Retrieval with Self-Supervision.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies InsCLR: Improving Instance Retrieval with Self-Supervision

Reference 11

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Observation 01ad9b93-0d6e-4703-81f7-7c2323ccee97 · outbound

This paper cites Deep Learning for Instance Retrieval: A Survey.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Deep Learning for Instance Retrieval: A Survey

Reference 12

Resolution
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Source-reported events for the cited work

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Observation a73d659b-1c51-4c1c-90db-585a93685a80 · outbound

This paper cites Understanding Human Object Vision: A Picture Is Worth a Thousand Rep- resentations.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Understanding Human Object Vision: A Picture Is Worth a Thousand Rep- resentations

Reference 13

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Observation f3639309-9223-4b46-9403-e0e745dc41ec · outbound

This paper cites How does the brain solve visual object recognition? Neuron 2012, 73, 415–434.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies How does the brain solve visual object recognition? Neuron 2012, 73, 415–434

Reference 14

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Observation e3501778-adcf-455a-89f7-16867caeb119 · outbound

This paper cites Recent advances in understanding object recognition in the human brain: Deep neural networks, temporal dynamics, and context.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Recent advances in understanding object recognition in the human brain: Deep neural networks, temporal dynamics, and context

Reference 15

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Observation 274f1c71-8141-43ff-b544-0c1730a89397 · outbound

This paper cites Dive into the details of self-supervised learning for medical image analysis.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Dive into the details of self-supervised learning for medical image analysis

Reference 16

Resolution
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Observation 4fe64e74-dabb-4b6c-a6fe-4ae43e6e8569 · outbound

This paper cites Unsupervised learning of disentangled representation via auto-encoding: A survey.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Unsupervised learning of disentangled representation via auto-encoding: A survey

Reference 17

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Observation f9771df5-f8b2-412c-adc6-16d8889e676d · outbound

This paper cites A simple framework for contrastive learning of visual repre- sentations.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies A simple framework for contrastive learning of visual repre- sentations

Reference 18

Resolution
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Source-reported events for the cited work

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Observation 627e979b-8809-4902-a120-77fa86f5bdf6 · outbound

This paper cites Momentum Contrast for Unsupervised Visual Representation Learning.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Momentum Contrast for Unsupervised Visual Representation Learning

Reference 19

Resolution
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Observation 65835a96-0b6b-4550-9504-84b1ae266992 · outbound

This paper cites VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Reference 20

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Observation a26bf9d3-c909-471d-b210-8186ef5a46da · outbound

This paper cites Masked Autoencoders Are Scalable Vision Learners.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Masked Autoencoders Are Scalable Vision Learners

Reference 21

Resolution
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Observation 0d63dcb7-b0de-48f8-b1ef-ec36dc7d1fff · outbound

This paper cites Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language

Reference 22

Resolution
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Observation 2eb1b6d3-a01b-4acc-b6ef-6f2909722b44 · outbound

This paper cites On the duality between contrastive and non-contrastive self-supervised learning.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies On the duality between contrastive and non-contrastive self-supervised learning

Reference 23

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Observation e8797ff7-9340-4eb6-b2c4-aaa91242c91a · outbound

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

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 24

Resolution
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Observation 8bd713fc-7779-4fa7-b403-cdda1e68ba33 · outbound

This paper cites Emerging Properties in Self-Supervised Vision Transformers.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Emerging Properties in Self-Supervised Vision Transformers

Reference 25

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Observation dd0115c1-40b7-4360-a030-c6bb100533c2 · outbound

This paper cites Learning vision from models rivals learning vision from data.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Learning vision from models rivals learning vision from data

Reference 26

Resolution
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This paper cites ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation

Reference 27

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Source-reported events for the cited work

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Observation 0c438559-6260-47e4-b18c-f290918c6442 · outbound

This paper cites Learning disentangled representations in the imaging domain.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Learning disentangled representations in the imaging domain

Reference 28

Resolution
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Observation 1093e46a-118c-4da3-a584-610cb903068c · outbound

This paper cites Disentangled Representation Learning.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Disentangled Representation Learning

Reference 29

Resolution
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Observation f4dc4822-d8fa-4f0c-889d-204431deab64 · outbound

This paper cites Challenging common assumptions in the unsupervised learning of disentangled representations.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Challenging common assumptions in the unsupervised learning of disentangled representations

Reference 30

Resolution
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Source-reported events for the cited work

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Observation 90d45a48-02a5-4744-b74d-cce9ea4e91ab · outbound

This paper cites ClusterGAN: Latent Space Clustering in Generative Adversarial Networks.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies ClusterGAN: Latent Space Clustering in Generative Adversarial Networks

Reference 31

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Observation 65d6c4ff-00b6-44dc-b4df-77ce5dee6ef3 · outbound

This paper cites Simple disentanglement of style and content in visual representations.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Simple disentanglement of style and content in visual representations

Reference 32

Resolution
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Observation 3f6dff96-fa19-4d58-bd27-d46bfadf0f42 · outbound

This paper cites Generating diverse high-fidelity images with VQ-V AE-2.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Generating diverse high-fidelity images with VQ-V AE-2

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:44:37.043804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.911453Z digest=sha256:6750a9fa4ba53a7b60d01f8e043dec3a86a50a1d2886c9063fca702eaf33f759

Observation 6b6b335d-bb4e-4e65-91ba-a638d905d08e · outbound

This paper cites Taming Transformers for High-Resolution Image Synthesis.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Taming Transformers for High-Resolution Image Synthesis

Reference 34

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T15:44:35.821873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.915859Z digest=sha256:6456226cdc2f957f6dce775ee3fcf621d7cf81c1c63bec3b3b88c250344e9f61

Observation 3677947d-d5f7-43ec-b539-58e5ec6f138e · outbound

This paper cites Disentangled representation learning in cardiac image analysis.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Disentangled representation learning in cardiac image analysis

Reference 35

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T15:44:35.565536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.920463Z digest=sha256:c6518d63ddbc0625f1fa490ce588103c562d8863be468db0cbfa12ecd1973993

Observation 4b176b63-c8d9-4b1f-8888-44a9e2903148 · outbound

This paper cites RetCCL: Clustering- guided contrastive learning for whole-slide image retrieval.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies RetCCL: Clustering- guided contrastive learning for whole-slide image retrieval

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:44:37.028751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.924982Z digest=sha256:a7faf479f86ce52bb9a98ba7418b676f7e56e9ac9f80fc1592f42789bad063ab

Observation 39054587-61e9-4763-869c-b34eb611f979 · outbound

This paper cites Self-supervised contrastive learning with random walks for medical image segmentation with limited annotations.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Self-supervised contrastive learning with random walks for medical image segmentation with limited annotations

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:44:37.013151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.929395Z digest=sha256:73e82c81069e35da95aa06d586f1b762472d5a86f535fd2edc3374f59550f684

Observation d0b88c41-6f85-46cc-87e4-3e9df9243e8d · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Categorical Reparameterization with Gumbel-Softmax

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:44:36.993484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.933718Z digest=sha256:485cead38b1870e037272b7ea3e0cf8d337f7a263ba909184f44722ad81cf2f8

Observation d6e76bff-d32c-42c7-b50e-4e983c62dc6a · outbound

This paper cites Semantic Image Synthesis with Spatially-Adaptive Normalization.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Semantic Image Synthesis with Spatially-Adaptive Normalization

Reference 39

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T15:44:35.397796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.937979Z digest=sha256:ad3d8d6b80e7188c11683de93e513dd838fd3683185509d528d1ca36359196bf

Observation 785314c5-0a4a-474c-8c07-65af79e0da5c · outbound

This paper cites Self-supervised learning for medical image analysis: Discriminative, restorative, or adversarial? Med Image Anal.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Self-supervised learning for medical image analysis: Discriminative, restorative, or adversarial? Med Image Anal

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:44:36.978575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.942502Z digest=sha256:a03cc302a1c2dbb34154b57c323305b435ade9c8f2d97349d1ca6a94fc324510

Observation 92b3edb5-fbea-481a-a219-9ad9edbea295 · outbound

This paper cites Light-Weight RefineNet for Real-Time Semantic Segmentation.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Light-Weight RefineNet for Real-Time Semantic Segmentation

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-09T15:44:35.134744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.947065Z digest=sha256:999aaa864be7f7c1aaea3ea7cb6b37cdb0a076230df4aba6f9e319e47a0017ae

Observation 8e5bda03-409a-4aa9-abef-ecccecf4642f · outbound

This paper cites Sketch-based semantic retrieval of medical images.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Sketch-based semantic retrieval of medical images

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:44:36.963309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.951893Z digest=sha256:0bf3d43ed36ede3484159e463062396756d557237d4329843dc1ee91287544da

Observation 598c3fa9-4865-4383-9066-258e69765538 · outbound

This paper cites Large-scale retrieval for medical image analytics: A comprehensive review.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Large-scale retrieval for medical image analytics: A comprehensive review

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:44:36.947575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.956872Z digest=sha256:0c66aa9b85d53ffd1aabdbe6a58c9aac5dcc267ee4497440a1dccd91e1ab850c

Observation 3df08e71-be10-4b16-a4c3-2c7e4a28ef66 · outbound

This paper cites A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-09T15:44:34.961288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:44:34.961288Z digest=sha256:e5de54a70004b0ce4e61c5778b71305d40dc3b8b13939cd6c3514114edde3552

Observation c3f65995-2ce6-4387-a69b-4e8f9e67c8b7 · outbound

This paper cites Back to the Basics: Revisiting Out-of-Distribution Detection Baselines.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Back to the Basics: Revisiting Out-of-Distribution Detection Baselines

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-09T15:44:35.090625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.966278Z digest=sha256:c09da1a6178bed43d222efa9af85599d4383d969a67067d5bc21745081c394c5

Observation e0a154f1-bcb2-4f14-aaf8-2d5d147e3efd · outbound

This paper cites Normalizing Flows: An Introduction and Review of Current Methods.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Normalizing Flows: An Introduction and Review of Current Methods

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-09T15:44:34.970843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:44:34.970843Z digest=sha256:7e8f709ec83fffe99236229d131b5ce9076040afdace6d99466ab3c53ae20773

Observation f1b9e9b1-0be4-45bc-8f5f-204810a344c5 · outbound

This paper cites On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-09T15:44:34.975491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:44:34.975491Z digest=sha256:c04236880d04217a55bb895766228c62f7a90bf28f9b9e37fabbc6ecb5091702

Observation 06a7b697-e1cb-4a2f-9282-9ad8c6c6620e · outbound

This paper cites Fast r-cnn.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Fast r-cnn

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:44:36.932080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.979878Z digest=sha256:00bccc8b2df75ebc71ffab0ba58ff680daa20f0a5bdc9a75646d79df10b0e575

Observation b877f547-cb50-452e-bbc5-9bece0c7b1cd · outbound

This paper cites Variability of echocardiographic measures of left ventricular diastolic function.

ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Variability of echocardiographic measures of left ventricular diastolic function

Reference 49

Resolution
verified exact
doi, observed 2026-08-09T15:44:35.020868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T15:44:34.983549Z digest=sha256:cba039c02c5f072c8a1c4a69e455963f70bb520748b1491d2cf16b37953cc043

Pith citing papers

No inbound Pith citation observations are available.