Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T08:32:42.583980Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2607.21088.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T08:32:42.583980Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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
39 of 39 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation f68bee1d-4460-4ec1-ae46-62cebadb3cf3 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Investigating the spatio-temporal distribution of gravity wave potential energy over the equatorial region using the era5 reanalysis data,
Reference 1
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Unavailable: canonical work link unavailable.
Observation e83cc9c5-ee1c-408b-bd68-a99a7ed2d65e · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data The Intrinsic Dimension of Images and Its Impact on Learning
Reference 2
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Observation ebd2c381-3c38-410e-b8b7-a3d624b83405 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep convolutional recurrent autoencoders for learning low-dimensional feature dynamics of fluid systems
Reference 3
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Observation cfce9c33-9e5b-4e43-a6cd-c72a69cacbd7 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Ldmnet: Low dimensional manifold regularized neural networks,
Reference 4
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Observation b6c8e1e4-ed49-473e-b733-d667ed2e466f · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Principal component analysis (pca),
Reference 5
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Observation 210cf9be-f411-4513-82af-e093c19cd6dd · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Stochastic sparse subspace clustering,
Reference 6
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Observation 57e31527-2f12-48b1-917d-da623c0863ea · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Robust recovery of subspace structures by low-rank representation,
Reference 7
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Observation 60990e96-1139-41ea-95d8-28ab4630ddd5 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data A selective overview of recent ad- vances in spectral clustering and their applications,
Reference 8
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Observation abee563b-2a9f-4922-877a-64605397777c · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Survey of spectral clustering based on graph theory,
Reference 9
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Observation 55c43007-4b99-4554-89a7-9005c354a76d · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep spectral cluster- ing using dual autoencoder network,
Reference 10
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Observation 3f813ae3-3573-4b5a-b905-c9043a62e45e · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Multi-scale fusion subspace clustering using similarity constraint,
Reference 11
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Observation 2a031456-b394-4a45-9a86-9e941e702f52 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Lrsc: Learning representations for subspace clustering,
Reference 12
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Observation ac3090ff-32d2-4847-a4b0-d2b5a94c054e · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep subspace clus- tering networks,
Reference 13
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Observation 82ff50c6-0e2b-4095-9fe9-13214d4aba53 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Scalable deep k- subspace clustering,
Reference 14
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Unavailable: canonical work link unavailable.
Observation 6b798024-a777-44ee-9138-7f4a5ccff372 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Large-scale subspace clustering via k-factorization,
Reference 15
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Unavailable: canonical work link unavailable.
Observation 37dded1b-2e91-4fbf-9804-7e8e4f4a848d · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Learning a self-expressive network for subspace clustering,
Reference 16
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Unavailable: canonical work link unavailable.
Observation 3a1541f1-c6dd-429f-ac97-ed515429a59d · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data U-net: Convolutional networks for biomedical image segmentation,
Reference 17
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Unavailable: canonical work link unavailable.
Observation 9f85d9ef-6a20-46d8-979a-790e2c0e8827 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Faconvlstm: Factorized-attention convlstm for efficient feature extraction in multivariate climate data,
Reference 18
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Unavailable: canonical work link unavailable.
Observation 72ed6c49-3bfb-4799-96dd-49bd34bacede · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep self-representative subspace clustering network,
Reference 19
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Unavailable: canonical work link unavailable.
Observation 71ee9364-69b2-49c0-ba11-74fd396b3d76 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep double self-expressive subspace clustering,
Reference 20
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Unavailable: canonical work link unavailable.
Observation 4cd95478-8367-41d1-bac4-ff3260a3dd16 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep adversarial subspace clustering,
Reference 21
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Unavailable: canonical work link unavailable.
Observation bf08c663-86bb-4603-a33e-8bd614c84ac9 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Clustergan: Latent space clustering in generative adversarial networks,
Reference 22
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Unavailable: canonical work link unavailable.
Observation c6576d82-704a-4a63-bd26-ba64ac29489f · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Gan- based enhanced deep subspace clustering networks,
Reference 23
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Unavailable: canonical work link unavailable.
Observation a9a0e6bf-e9aa-4fe1-80bc-98d516adf233 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Unsupervised deep embedding for clustering analysis,
Reference 24
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Unavailable: canonical work link unavailable.
Observation 26d26353-7a7a-4bf6-b29c-c46ad3160efe · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep Spatiotemporal Clustering: A Temporal Clustering Approach for Multi-dimensional Climate Data
Reference 25
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Unavailable: canonical work link unavailable.
Observation 8e091309-69ff-455c-8611-15f9b383acd9 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep learning for precipitation nowcasting: A benchmark and a new model,
Reference 26
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Unavailable: canonical work link unavailable.
Observation 93bc500c-0e2b-4c81-b6d8-623e1b7cf5fd · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep learning for arctic sea ice prediction,
Reference 27
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Unavailable: canonical work link unavailable.
Observation 6cd1ea5f-5ace-4aba-b23b-a69536b6cd23 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Spatiotemporal deep learning for regional climate downscaling,
Reference 28
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Unavailable: canonical work link unavailable.
Observation 31c8476d-2d65-46c2-989f-4f4159f4211a · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Auto-Encoding Variational Bayes
Reference 29
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Unavailable: canonical work link unavailable.
Observation 06be7b0d-57f2-46c6-bb92-b4814bbe9526 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data climate.copernicus.eu
Reference 30
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Unavailable: canonical work link unavailable.
Observation 6d347355-17e4-47a3-9d16-546440d7dcc9 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Era5 hourly data on single levels from 1940 to present
Reference 31
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Unavailable: canonical work link unavailable.
Observation 7b46636b-ec5c-4a7b-85cf-ca39d47e05e1 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Daily atmospheric observations
Reference 32
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Observation d0c77265-2702-450a-890c-31a3bd850266 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Deep tem- poral clustering: Fully unsupervised learning of time-domain features,
Reference 33
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Unavailable: canonical work link unavailable.
Observation b3493606-8abf-4f36-88dc-f505e40df858 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Cluster quality analysis using silhouette score,
Reference 34
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Observation 524c4359-31a4-4bbf-8c71-8cb1413da142 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Pdbi: A partitioning davies-bouldin index for clustering evaluation,
Reference 35
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Observation 33de6616-2ee9-40ab-afc2-ef7c4a71d1ab · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data An improved index for clustering validation based on silhouette index and calinski-harabasz index,
Reference 36
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Unavailable: canonical work link unavailable.
Observation 77fdefef-8efd-4a1f-bd5f-176cf9a2daa7 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Cluster analysis, wiley,
Reference 37
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Observation 5bafa6d9-299a-4bdb-8243-2e0536f9316c · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Unresolved cited work
Reference 38
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Observation 28483682-6c4e-4f76-9049-643d07c391e2 · outbound
CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data Advantages of the mean absolute error (mae) over the root mean square error (rmse) in assessing average model performance,
Reference 39
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No inbound Pith citation observations are available.