Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T15:44:34.983549Z
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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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
- Resolution
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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
- Resolution
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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
- Resolution
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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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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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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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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
- Resolution
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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
- Resolution
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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
- Resolution
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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
- Resolution
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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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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
- Resolution
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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
- Resolution
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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
- Resolution
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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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Observation aac26566-80b7-449d-b658-d50807cedd37 · outbound
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
- Resolution
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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
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Observation 1093e46a-118c-4da3-a584-610cb903068c · outbound
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ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Disentangled Representation Learning
Reference 29
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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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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
- Resolution
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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
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ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies Taming Transformers for High-Resolution Image Synthesis
Reference 34
- Resolution
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
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.
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.
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 2026-08-11T06:34:44.6726+00:00.
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 2026-08-11T06:34:44.6726+00:00.
Pith citing papers
No inbound Pith citation observations are available.