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Paper Citation Record · LEDGER

InDeed: Interpretable image deep decomposition with guaranteed generalizability

As of 14 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 0 inbound Pith citation observations for arXiv:2501.01127.

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

pith.paper-citation-record.v1
2501.01127 v1

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measured 86 of 86 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

86 of 86 outbound references displayed

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External citation measurements

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Outbound references

Observation f751824a-47d2-4de6-a782-769f28ea9de4 · outbound

This paper cites Deep image prior,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Deep image prior,

Reference 1

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This paper cites Structure-texture image decomposition using deep variational priors,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Structure-texture image decomposition using deep variational priors,

Reference 2

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This paper cites Double-dip: unsu- pervised image decomposition via coupled deep-image-priors,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Double-dip: unsu- pervised image decomposition via coupled deep-image-priors,

Reference 3

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This paper cites A review of image denoising algorithms, with a new one,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability A review of image denoising algorithms, with a new one,

Reference 4

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This paper cites Nonlinear total variation based noise removal algorithms,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Nonlinear total variation based noise removal algorithms,

Reference 5

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Observation 87850ef4-7429-40ad-9404-b2250a7bb70a · outbound

This paper cites Robust principal component analysis?.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Robust principal component analysis?

Reference 6

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This paper cites Ouahabi, Signal and image multiresolution analysis.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Ouahabi, Signal and image multiresolution analysis

Reference 7

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Observation 56bc265b-f335-4430-8e33-a079edf784c6 · outbound

This paper cites Sparse Bayesian Methods for Low-Rank Matrix Estimation,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Sparse Bayesian Methods for Low-Rank Matrix Estimation,

Reference 8

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Observation de7dd70c-f66f-4950-83bb-ca54d9973a25 · outbound

This paper cites Bilateral filtering for gray and color images,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Bilateral filtering for gray and color images,

Reference 9

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Observation 746a6d62-22c6-497c-ad96-99a3ce0aa24e · outbound

This paper cites Structure extraction from texture via relative total variation,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Structure extraction from texture via relative total variation,

Reference 10

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This paper cites Image decomposition combining low-rank and deep image prior,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Image decomposition combining low-rank and deep image prior,

Reference 11

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This paper cites Internal statistics of a single natural image,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Internal statistics of a single natural image,

Reference 12

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This paper cites Didfuse: deep image decomposition for infrared and visible image fusion,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Didfuse: deep image decomposition for infrared and visible image fusion,

Reference 13

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This paper cites Darn: a deep adversarial residual network for intrinsic image decomposition,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Darn: a deep adversarial residual network for intrinsic image decomposition,

Reference 14

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InDeed: Interpretable image deep decomposition with guaranteed generalizability A survey on neural network interpretability,

Reference 15

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This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,

Reference 16

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Algorithm unrolling: Inter- pretable, efficient deep learning for signal and image processing,

Reference 17

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Deep proximal unrolling: Algorithmic framework, convergence analysis and ap- plications,

Reference 18

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InDeed: Interpretable image deep decomposition with guaranteed generalizability An unsupervised deep unrolling framework for constrained op- timization problems in wireless networks,

Reference 19

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Interpretable convolutional neural networks,

Reference 20

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Bayeseg: Bayesian modeling for medical image segmentation with interpretable gen- eralizability,

Reference 21

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Simplified pac-bayesian margin bounds,

Reference 22

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Statistical guarantees for variational autoencoders using pac-bayesian theory,

Reference 23

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Stable princi- pal component pursuit,

Reference 24

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Exact matrix completion via convex optimization,

Reference 25

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Robust prin- cipal component analysis: A factorization-based approach with linear complexity,

Reference 26

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Fast convex optimization algorithms for exact recovery of a corrupted low-rank matrix,

Reference 27

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InDeed: Interpretable image deep decomposition with guaranteed generalizability The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices

Reference 28

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Nonparametric bayesian matrix completion,

Reference 29

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Rank-One Network: An Effective Frame- work for Image Restoration,

Reference 30

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InDeed: Interpretable image deep decomposition with guaranteed generalizability A non-local algorithm for image denoising,

Reference 31

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Image denoising via sparse and redun- dant representations over learned dictionaries,

Reference 32

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Pseudo 3d auto-correlation network for real image denoising,

Reference 34

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Nbnet: Noise basis learning for image denoising with subspace projec- tion,

Reference 36

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Deep image demosaicking using a cascade of convolutional residual denoising networks,

Reference 37

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InDeed: Interpretable image deep decomposition with guaranteed generalizability Deeply-recursive convolutional network for image super-resolution,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.455040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.532347Z digest=sha256:8937ac6c3e1dc218fc656027ac98c8c37d901f7ac643275f4bb4ba3fc4514380

Observation 65b04ff0-d4cf-42ec-943c-9da13a8b146b · outbound

This paper cites Blind universal bayesian image denoising with gaussian noise level learning,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Blind universal bayesian image denoising with gaussian noise level learning,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.441281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.536581Z digest=sha256:9f76f314780707e628cae378779f8456f0e083ea012ef647debd1c1a106838ea

Observation a83a19a1-bd13-4cc9-ab2a-8adb72c7344e · outbound

This paper cites A high-quality de- noising dataset for smartphone cameras,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability A high-quality de- noising dataset for smartphone cameras,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.427764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.540936Z digest=sha256:48d97c5cd1b0b0702c6389a000953a9bbc215356a5c3e1f19708c25f3c7170de

Observation 4f79f9c8-0520-40b1-afca-152667ceb568 · outbound

This paper cites Unrolling of deep graph total variation for image denoising,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Unrolling of deep graph total variation for image denoising,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.413732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.545479Z digest=sha256:105c115985572400cd1529b0424a45de6d8bb44048ab3f15b739954e19ffd0e7

Observation e77d8771-f019-4958-9aaf-4aec6f3e085a · outbound

This paper cites Residual denoising diffusion models,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Residual denoising diffusion models,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.400356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.549593Z digest=sha256:32bc105e37f354475f2bd1715692cb675ead6ed4b6752d9ae63d2226a61efcf3

Observation cc0b8c9f-cea9-4277-bde4-fedbc53b40da · outbound

This paper cites Masked image training for generalizable deep image denoising,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Masked image training for generalizable deep image denoising,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.387445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.553897Z digest=sha256:25939ea29386024f94e282d8d327a625470a7a42fe5feb89edc4de584a3c863f

Observation 72f9d335-07ce-4e59-8090-a9d2ebe10ee5 · outbound

This paper cites DRÆM – A discrim- inatively trained reconstruction embedding for surface anomaly detection,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability DRÆM – A discrim- inatively trained reconstruction embedding for surface anomaly detection,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.374023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.558556Z digest=sha256:4bb255d8041df98970edf92d9a17915dc2d67f99735a7e6192ec58edc7689933

Observation 6f29091c-7872-4bbe-9e7b-bb4fa187de46 · outbound

This paper cites Anomaly detection in video via self-supervised and multi-task learning,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Anomaly detection in video via self-supervised and multi-task learning,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.360516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.563172Z digest=sha256:c800f4a1c6ffac556c178b7370443ddc65b9bee86cfeac0832a2f8362846ebbf

Observation 8a6be9be-4b54-4af6-a742-28ce39bf8c90 · outbound

This paper cites Anomaly detection with domain adaptation,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Anomaly detection with domain adaptation,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.347533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.567771Z digest=sha256:ad4fcf37518a1dc31398ae0c6a680f566ab89bf7661dd770f9996088b8f5f47f

Observation 42d2bd28-0f7c-4a1f-91d1-9acceb453004 · outbound

This paper cites A unified model for multi-class anomaly detection,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability A unified model for multi-class anomaly detection,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.334368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.572415Z digest=sha256:c2c5ef0371c5b5aff82f5968332c9c402f3b64fa750056534f03f0ac08ed02e7

Observation 621a3bb5-e770-41a5-9c1c-f70faa747007 · outbound

This paper cites Self-supervised predictive convolu- tional attentive block for anomaly detection,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Self-supervised predictive convolu- tional attentive block for anomaly detection,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.320825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.576855Z digest=sha256:65ed9af5b605dfacdf87744cc59939323ded73ecb31b0c7130b28c93c975b7a3

Observation 00f2db8c-668a-4014-9718-40d1d1c59961 · outbound

This paper cites Skip- ganomaly: Skip connected and adversarially trained encoder- decoder anomaly detection,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Skip- ganomaly: Skip connected and adversarially trained encoder- decoder anomaly detection,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.307398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.581046Z digest=sha256:3454c27ce70f5a4efdeaa5c3ecc4808c6c49d29bd13f56d8d9fe22dd438dd08a

Observation 8f34ab4a-8db7-4c98-86cc-1771bcfd5bd6 · outbound

This paper cites Learning temporal regularity in video sequences,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Learning temporal regularity in video sequences,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.294267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.585441Z digest=sha256:ac3a0bd35c07e7a3d473a4560716004217cb53ab3838597bfa2b024bdd51a3b4

Observation 0d053950-b95c-4941-b213-1aa85767736f · outbound

This paper cites Anomaly localization by modeling perceptual features.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Anomaly localization by modeling perceptual features

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T22:39:53.589904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:39:53.589904Z digest=sha256:ba6cea1b70d2ee617a92d8526b2376a86ed3456dfdcb61d62504e60786044774

Observation 9bd9c79b-702d-4f79-845b-a1289725dcd8 · outbound

This paper cites A hybrid video anomaly detection framework via memory-augmented flow re- construction and flow-guided frame prediction,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability A hybrid video anomaly detection framework via memory-augmented flow re- construction and flow-guided frame prediction,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.280865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.594773Z digest=sha256:07af56d4a6f9e0f20ec8be380e54b141fc9839c066a3a4642443a58f650a0c81

Observation 2b2c18f6-7d21-4629-be84-46e9ffd4b4d4 · outbound

This paper cites FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows.

InDeed: Interpretable image deep decomposition with guaranteed generalizability FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows

Reference 53

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unresolved
no resolver link, observed 2026-08-10T22:39:53.598882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:39:53.598882Z digest=sha256:643dde05b7b2ca5218cbc232bcc139b5bb4e82ae9cdabd4f1b1b230b9f398bcb

Observation 06be7236-6475-4e9d-8011-dc56e3f0d4c9 · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Improved Regularization of Convolutional Neural Networks with Cutout

Reference 54

Resolution
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no resolver link, observed 2026-08-10T22:39:53.603450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:39:53.603450Z digest=sha256:7a562ebaf1a1555b3048741f7abf12bc7e6a5b2292390c55e6867260cc527bf5

Observation d18adbf4-074d-495c-8a91-dc086cb54919 · outbound

This paper cites Cutpaste: Self-supervised learning for anomaly detection and localization,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Cutpaste: Self-supervised learning for anomaly detection and localization,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.267607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.607823Z digest=sha256:104fc3b00a3312ec294b05b4f63c031ce97094301765a807b798b29301d72d3f

Observation fae7e46e-db31-4e71-85b4-d70408e02aea · outbound

This paper cites Superpixel masking and inpainting for self-supervised anomaly detection.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Superpixel masking and inpainting for self-supervised anomaly detection

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.254179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.611955Z digest=sha256:a87fa63d09d5089d7067712a4ad600a04b7e4a945648d241a2656e93de468b37

Observation ed7b8edd-c59d-4dd3-84ba-a4dc3eee204c · outbound

This paper cites Learning semantic context from normal samples for unsupervised anomaly detection,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Learning semantic context from normal samples for unsupervised anomaly detection,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.240743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.616353Z digest=sha256:8b84cc48bf2344eb103684dad5da6e1084d1e1652e5163f8af8755ad505c733e

Observation 0a1c6fce-b8ea-4372-b772-e09accc9cfe5 · outbound

This paper cites Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.226513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.620665Z digest=sha256:b0401d525f205f8c706b67da5aaf935273517632cd0d63d77114b9fd060deac6

Observation 877cf30f-69ba-443a-a9e4-0acbba77ae4d · outbound

This paper cites Deep learning for anomaly detection: A review,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Deep learning for anomaly detection: A review,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.211506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.625146Z digest=sha256:77b0210a58f3f16dbd876c5fa2e8413785e612113ec0b89cfbc69e059e2ca75d

Observation 2ddbabea-17b1-45db-b1a2-46c30f15516c · outbound

This paper cites Hics: High contrast subspaces for density-based outlier ranking,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Hics: High contrast subspaces for density-based outlier ranking,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.197239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.630367Z digest=sha256:b79ae65f4bbe4e1cf7c686eba92dfd183efc0664b4b45a47c459a18f33ba26b0

Observation e6c8c7ec-bbc1-4e1c-8c84-944424f497dc · outbound

This paper cites Variational infer- ence: A review for statisticians,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Variational infer- ence: A review for statisticians,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.183093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.634908Z digest=sha256:5a6c84ea1d95152d32db93f2344d81f01fa2116a435d0f44195f449ce670ea44

Observation c05573ad-4755-40d6-bc3e-107ae46ff988 · outbound

This paper cites Advances in variational inference,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Advances in variational inference,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.169538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.639102Z digest=sha256:c80264925eb6c6e70ec8a56650b2280fdbd48a9d173c359f8dcf040a8768365d

Observation 40bb859c-56f5-4c98-923d-3d4a17eecb35 · outbound

This paper cites No free lunch theorems for optimization,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability No free lunch theorems for optimization,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.155288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.643601Z digest=sha256:fec143fb1a521cc738dd55074d02259e96d9ff080be16a3a9edc4144c048797c

Observation 0db98856-e380-4170-ad5c-7f15c9972bcc · outbound

This paper cites A model of inductive bias learning,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability A model of inductive bias learning,

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T22:39:53.648026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:39:53.648026Z digest=sha256:015a3ec1eac75e48738f6b0c593674d4dbfe1827d852cf73a3319bd492676901

Observation dcbe5db4-6ad1-4aba-b80a-ef10a3670332 · outbound

This paper cites Inductive biases for deep learning of higher-level cognition,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Inductive biases for deep learning of higher-level cognition,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.132869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.652306Z digest=sha256:2d2c503efe9bc7ee2f9f988b18f5732835f0954e37a23218c3fac6049d499d3e

Observation 669a2035-7ed5-4459-9d30-11648050aab0 · outbound

This paper cites Bayesian image super-resolution with deep modeling of image statistics,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Bayesian image super-resolution with deep modeling of image statistics,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.118462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.656839Z digest=sha256:13bef5d5526fb51903729f6451601c191109b38217b94a23cd54e4eb205b5ab4

Observation 0be894c6-b9bd-4975-bf97-929f80909e78 · outbound

This paper cites Tutorial on Variational Autoencoders.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Tutorial on Variational Autoencoders

Reference 67

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no resolver link, observed 2026-08-10T22:39:53.661324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:39:53.661324Z digest=sha256:6900fa1f3bedb519a1b8d4bac79be4b34a7e2f4e54c9a451f8de5eff459f807c

Observation 4e555c00-1f5c-44be-a887-7cf17052be86 · outbound

This paper cites Deep residual learning for image recognition,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Deep residual learning for image recognition,

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T22:39:53.666389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:39:53.666389Z digest=sha256:7574b10b52118cfd630f105feea6ed4046e31583a219801325f51ee20b20c7d5

Observation 0be80319-df29-4697-8c30-1eb3338fcc9a · outbound

This paper cites Pac- bayesian theory meets bayesian inference,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Pac- bayesian theory meets bayesian inference,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.094653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.670675Z digest=sha256:22472ddbb2cb824bd64023904bd61e3517791fc3e63c1856e83c98a6e07d0d05

Observation 32731f1a-7468-43db-a7fb-c877e00b150b · outbound

This paper cites Efficient and accurate estimation of lipschitz constants for deep neural networks,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Efficient and accurate estimation of lipschitz constants for deep neural networks,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.080454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.675129Z digest=sha256:ad515651521b857a8280f19ca79aa7aa7ea1bd69bca6e07afafab3211238f191

Observation 1bf9bcdd-cac1-4683-ad46-8ae38fbd43bb · outbound

This paper cites Optimal adaptation for early stopping in statistical inverse problems,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Optimal adaptation for early stopping in statistical inverse problems,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.066616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.679728Z digest=sha256:6134a3caf2eb37f3d75a9018eadc01c1189d96093e58b161f33466c2ab619c7e

Observation 70b7424e-836a-4d92-805b-c812992b2445 · outbound

This paper cites Ntire 2017 challenge on single image super-resolution: Dataset and study,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Ntire 2017 challenge on single image super-resolution: Dataset and study,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.052607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.684300Z digest=sha256:05bd370d52a7e82a44cb4e6a1d1c2d4b0ca2ce4b3c8718192f0167a1e385ed33

Observation 60a0d809-25b9-4bef-bc3b-66507554653f · outbound

This paper cites Fields of experts: A framework for learning image priors,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Fields of experts: A framework for learning image priors,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.038655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T22:39:53.688462Z digest=sha256:fca9432edfebff656bb19f094ab321496ca2cc76ab261f35060627af79a46b3d

Observation a45d5720-f7bd-4bf0-926e-68fc5b8b0aa6 · outbound

This paper cites Kodak lossless true color image suite,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Kodak lossless true color image suite,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:39:54.022905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 02a78a25-a36e-4350-a730-ae316cfe39b9 · outbound

This paper cites Color demosaicking by local directional interpolation and nonlocal adaptive threshold- ing,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Color demosaicking by local directional interpolation and nonlocal adaptive threshold- ing,

Reference 75

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation bcaed63f-8be6-4560-844e-eba883ab7e1e · outbound

This paper cites Real-world Noisy Image Denoising: A New Benchmark.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Real-world Noisy Image Denoising: A New Benchmark

Reference 76

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a0fb5b59-c4d7-40ed-9f12-e6a654b1aa44 · outbound

This paper cites Mvtec ad– a comprehensive real-world dataset for unsupervised anomaly detection,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Mvtec ad– a comprehensive real-world dataset for unsupervised anomaly detection,

Reference 77

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8460c329-491d-4d30-ac35-f210d5189342 · outbound

This paper cites Steel defect detection,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Steel defect detection,

Reference 78

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation d23d7aca-0ee3-48f1-b63a-85cdf8b06bed · outbound

This paper cites A Benchmark of Medical Out of Distribution Detection.

InDeed: Interpretable image deep decomposition with guaranteed generalizability A Benchmark of Medical Out of Distribution Detection

Reference 79

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Unavailable: canonical work link unavailable.

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Observation 60021392-1d21-4f10-866a-ab040cb7019f · outbound

This paper cites The relationship between precision- recall and roc curves,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability The relationship between precision- recall and roc curves,

Reference 80

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 08a13444-a534-402e-b930-e91b8ec5be0a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Adam: A Method for Stochastic Optimization

Reference 81

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 82dd13a7-947f-435a-93b9-4b2ec9f80bd8 · outbound

This paper cites Image denois- ing by sparse 3-d transform-domain collaborative filtering,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Image denois- ing by sparse 3-d transform-domain collaborative filtering,

Reference 82

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2d04093b-b669-4d2d-a8ad-df1b23f10ad7 · outbound

This paper cites Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising,

Reference 83

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 3ee87fb0-f8aa-4255-8048-1ffceb02c55c · outbound

This paper cites Ffdnet: Toward a fast and flexible solution for cnn-based image denoising,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Ffdnet: Toward a fast and flexible solution for cnn-based image denoising,

Reference 84

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d773f380-1795-4bec-a552-3d52322ef5ff · outbound

This paper cites Rank-one network: An effective frame- work for image restoration,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Rank-one network: An effective frame- work for image restoration,

Reference 85

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 56c262f0-4527-4829-bf1f-3bc047e55db4 · outbound

This paper cites Deep variational network toward blind image restoration,.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Deep variational network toward blind image restoration,

Reference 86

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 91717b5a-5762-4bf5-b8b0-b40fb1d34787 · outbound

This paper cites Student-Teacher Feature Pyramid Matching for Anomaly Detection.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Student-Teacher Feature Pyramid Matching for Anomaly Detection

Reference 87

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9fc53c3a-832a-4dec-884a-38bed62da9f8 · outbound

This paper cites Shangqi Gao is a Research Associate at the University of Cambridge.

InDeed: Interpretable image deep decomposition with guaranteed generalizability Shangqi Gao is a Research Associate at the University of Cambridge

Reference 2021

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Pith citing papers

No inbound Pith citation observations are available.