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Paper Citation Record · LEDGER

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation

As of 11 August 2026, this Paper Citation Record lists 100 of 105 outbound references and 0 inbound Pith citation observations for arXiv:2502.08505.

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

pith.paper-citation-record.v1
2502.08505 v2

Coverage vector

measured 100 of 105 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:53:49.239186Z

measured 100 of 100 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

100 of 105 outbound references displayed

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External citation measurements

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Outbound references

Observation fa0237eb-b982-4328-9013-53482ba725b2 · outbound

This paper cites Tudataset: A collection of benchmark datasets for learning with graphs.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Tudataset: A collection of benchmark datasets for learning with graphs

Reference 1

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Observation 008692a8-e384-4899-a6a9-758a6fcef9df · outbound

This paper cites How powerful are graph neural networks? InProceedings of International Conference on Learning Representations, 2018.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation How powerful are graph neural networks? InProceedings of International Conference on Learning Representations, 2018

Reference 2

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Observation 6fc21127-88e4-4fb5-a877-8400fbff9956 · outbound

This paper cites Hierarchical graph representation learning with differentiable pooling.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Hierarchical graph representation learning with differentiable pooling

Reference 3

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Observation 87526b1f-ff5f-400e-9da9-e6e597feb6d8 · outbound

This paper cites kGCN: a graph-based deep learning framework for chemical structures.Journal of Cheminformatics, 12(1), 5 2020.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation kGCN: a graph-based deep learning framework for chemical structures.Journal of Cheminformatics, 12(1), 5 2020

Reference 4

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Observation 6cbb66c0-432d-4c18-b279-1ef9d222bbc3 · outbound

This paper cites Kipf and Max Welling.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Kipf and Max Welling

Reference 5

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Observation 3e70fc57-4c71-4b11-b7c4-093ebaa44924 · outbound

This paper cites Inductive representation learning on large graphs.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Inductive representation learning on large graphs

Reference 6

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Observation 3e4ec2cb-6a87-4663-adcc-df79b9ab0839 · outbound

This paper cites Improving graph neural networks with learn- able propagation operators.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Improving graph neural networks with learn- able propagation operators

Reference 7

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Observation 059281d1-d531-4cf8-baa7-fc2a2e776a8f · outbound

This paper cites Agent-based graph neural networks.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Agent-based graph neural networks

Reference 8

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Observation 658abe10-773d-46d0-890e-62aabb59a89f · outbound

This paper cites Schoenholz, Patrick F.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Schoenholz, Patrick F

Reference 9

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Observation 22dbb35c-f2b6-4b95-ae00-963df01519cb · outbound

This paper cites Graphattentionnetworks.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Graphattentionnetworks

Reference 10

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Observation df5ec495-6dbc-42ae-beeb-5b15b60bebfa · outbound

This paper cites Asgn: An active semi-supervised graph neural network for molec- ular property prediction.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Asgn: An active semi-supervised graph neural network for molec- ular property prediction

Reference 11

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Observation 189a261d-9ec0-42fc-9c9a-cabd46e52c4b · outbound

This paper cites Randomized schur complement views for graph contrastive learning.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Randomized schur complement views for graph contrastive learning

Reference 12

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Observation 9ca1a899-7853-4d28-9595-b48abf208ba3 · outbound

This paper cites SEGA: Structural entropy guided anchor view for graph contrastive learning.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation SEGA: Structural entropy guided anchor view for graph contrastive learning

Reference 13

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Observation f0d3f2d4-d38b-429f-8a09-f03f9272006d · outbound

This paper cites Transferable attention for domain adaptation.Proceedings of the AAAI Conference on Artificial Intelligence, 33(01): 5345–5352, Jul.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Transferable attention for domain adaptation.Proceedings of the AAAI Conference on Artificial Intelligence, 33(01): 5345–5352, Jul

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

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Observation 7420422d-4a7e-47a1-9829-844651b87b3a · outbound

This paper cites Domainadaptation in remote sensing image classification: A survey.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15:9842–9859, 2022.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Domainadaptation in remote sensing image classification: A survey.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15:9842–9859, 2022

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Observation d656460f-e6e8-4668-8089-fe7c8bc4ff9e · outbound

This paper cites Bridging Domains with Approximately Shared Features.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Bridging Domains with Approximately Shared Features

Reference 16

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Observation eb0e1e4f-4339-413f-8b17-54500ff4c0aa · outbound

This paper cites Near-optimal linear regression under distribution shift.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Near-optimal linear regression under distribution shift

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Observation 794d8d6e-3f68-4168-b69d-eeda5ff9d09d · outbound

This paper cites Controllable Prompt Tuning For Balancing Group Distributional Robustness.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Controllable Prompt Tuning For Balancing Group Distributional Robustness

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Observation 59a08265-1652-418a-a3ed-e3a4013386a2 · outbound

This paper cites Unsupervised domain adaptation for semantic image segmentation: a comprehensive survey, 2021.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Unsupervised domain adaptation for semantic image segmentation: a comprehensive survey, 2021

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Observation 4ba83623-a66d-4cb6-ac6d-98495f00c6ae · outbound

This paper cites Graph convolutional policy network for goal-directed molecular graph generation.Advances in neural information processing systems, 31, 2018.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Graph convolutional policy network for goal-directed molecular graph generation.Advances in neural information processing systems, 31, 2018

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Observation bbddd578-de5e-41da-b63a-79b128297718 · outbound

This paper cites Skipgnn: predicting molecular interactions with skip-graph networks.Scientific reports, 10(1):1–16, 2020.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Skipgnn: predicting molecular interactions with skip-graph networks.Scientific reports, 10(1):1–16, 2020

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Observation 96320fb6-c354-48d8-8eb1-a16960338b6c · outbound

This paper cites Does gnn pretraining help molecular representa- tion? Advances in Neural Information Processing Systems, 35:12096–12109, 2022.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Does gnn pretraining help molecular representa- tion? Advances in Neural Information Processing Systems, 35:12096–12109, 2022

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Observation ddb3e6d5-e951-44ab-996f-18d8e0382261 · outbound

This paper cites Graph domain adaptation via theory-grounded spectral regularization.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Graph domain adaptation via theory-grounded spectral regularization

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Observation 1d80af32-e47e-4dc5-a73f-bb187e939925 · outbound

This paper cites Domain-adversarial training of neural net- works.JournalofMachineLearningResearch ,17(59):1–35,2016.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Domain-adversarial training of neural net- works.JournalofMachineLearningResearch ,17(59):1–35,2016

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Observation 3243f5f1-ec55-4531-a690-20e8652d0eb0 · outbound

This paper cites Tuan Nguyen, Toan Tran, Yarin Gal, Philip Torr, and Atilim Gunes Baydin.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Tuan Nguyen, Toan Tran, Yarin Gal, Philip Torr, and Atilim Gunes Baydin

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Observation 5042c0fd-ef66-46b5-a5b3-27f26dd3aa34 · outbound

This paper cites A theory of label propagation for subpopulation shift.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation A theory of label propagation for subpopulation shift

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Observation 631461a6-3842-4a08-a0be-f26b5dd2fe7b · outbound

This paper cites HaoChen, Colin Wei, Ananya Kumar, and Tengyu Ma.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation HaoChen, Colin Wei, Ananya Kumar, and Tengyu Ma

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Observation ada3675f-5c38-4428-8db2-5464ad233de4 · outbound

This paper cites Tensor-view topological graph neural network.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Tensor-view topological graph neural network

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Observation 040da7ba-1873-4a56-8540-bbc121df18ab · outbound

This paper cites Structure- activity relationship of mutagenic aromatic and heteroaromatic nitro compounds.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Structure- activity relationship of mutagenic aromatic and heteroaromatic nitro compounds

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Observation fe0123ef-2f99-46fa-9d7b-d034e9580300 · outbound

This paper cites Visualizing data using t-sne.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Visualizing data using t-sne

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Source-reported events for the cited work

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Observation 43c4ff55-5f6b-4906-b886-7045b9ff7923 · outbound

This paper cites Conditionaladversarial domain adaptation.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Conditionaladversarial domain adaptation

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Observation 7bb82ed8-87bb-4f7a-a91a-2bb79e463937 · outbound

This paper cites Graph neural networks: A review of methods and applications.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Graph neural networks: A review of methods and applications

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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.

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Observation 728b465e-0057-4beb-b898-0a8819a35c8d · outbound

This paper cites Weisfeiler-lehman graph kernels.Journal of Machine Learning Research, 12(9), 2011.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Weisfeiler-lehman graph kernels.Journal of Machine Learning Research, 12(9), 2011

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Observation 35d5e98e-1a0a-4e89-a4bf-db8a21baf647 · outbound

This paper cites Graph learning: A survey.IEEE Trans AI, 2(2):109–127, 2021.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Graph learning: A survey.IEEE Trans AI, 2(2):109–127, 2021

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

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Observation c9cf0421-1fae-403a-a896-aba5d9f0ef6f · outbound

This paper cites Semi-supervised classification with graph convolutional networks.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Semi-supervised classification with graph convolutional networks

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raw_fallback, observed 2026-08-08T04:53:50.800321Z

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

source=pdf_text observed=2026-08-08T04:53:48.952220Z digest=sha256:9300950da6acda3ffc17dc18271d57905f4dd193d4f288a86ee2d4d07c89bfe4

Observation 27d8a508-f599-4177-9bcc-2781e8388ec9 · outbound

This paper cites Graph attention networks.Proceedings of International Conference on Learning Representations, 2018.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Graph attention networks.Proceedings of International Conference on Learning Representations, 2018

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verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.787450Z

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=2026-08-08T04:53:48.956498Z digest=sha256:95ca62ec1b07dca9f147daccdf2979e5126fb28224c93418ca896576a210e906

Observation cc1ff7ff-f3bf-4dac-a763-ba3daee0464c · outbound

This paper cites Towards sparse hierarchical graph classifiers.Workshop on Relational Representation Learning, NeurIPS, 2018.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Towards sparse hierarchical graph classifiers.Workshop on Relational Representation Learning, NeurIPS, 2018

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.774556Z

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=2026-08-08T04:53:48.960781Z digest=sha256:1a905c0d3590101c4fb6467b25d35a670cf9ece36a58892bc6f928d26680fe18

Observation 92f690a9-f7f1-4412-a38e-1326d2fac2db · outbound

This paper cites Graph u-nets.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Graph u-nets

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.761392Z

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=2026-08-08T04:53:48.965193Z digest=sha256:adb5312922e796ab00e6ba04f1fef81d4009886c6a674f4f10b4a2f0c475dec1

Observation 42d388d4-5968-4c8f-84cf-48f7aac1f06a · outbound

This paper cites an unresolved cited work.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Unresolved cited work

Reference 39

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unresolved
raw_fallback, observed 2026-08-08T04:53:50.747918Z

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=2026-08-08T04:53:48.969285Z digest=sha256:709f40fff4a2722dbe55fe1b587c8736df7303d28f99f90ec286fe1116efdc4a

Observation f6c3d995-6a71-4212-9b41-7df640f255ee · outbound

This paper cites Carrière, F.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Carrière, F

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.734849Z

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=2026-08-08T04:53:48.973560Z digest=sha256:215185dc75bc7b7e0df4e146dc4036588e052ab19b3a29e26eb3026fe3c92d3d

Observation f4dec5ff-0216-4881-b04d-3613678bf02a · outbound

This paper cites Going beyond persistent homology using persistenthomology.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Going beyond persistent homology using persistenthomology

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.721018Z

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=2026-08-08T04:53:48.977735Z digest=sha256:cfbbf0257c3117560c6b74fe38d1d4ba370f0620e049c34af4ffa2a1b192dff3

Observation 992fbbb7-017c-4bb9-b692-e26d49717fb7 · outbound

This paper cites Adapting visual category models to new domains.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Adapting visual category models to new domains

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.706858Z

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=2026-08-08T04:53:48.982045Z digest=sha256:205a0525cf6f69b37e1b6c1b83cc88075abe66390877be7a4738a46274f72b61

Observation a61312bd-d93f-4e9c-9e84-6458fb18c6e2 · outbound

This paper cites Unsupervised domain adaptation by backpropagation.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Unsupervised domain adaptation by backpropagation

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.693180Z

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=2026-08-08T04:53:48.986120Z digest=sha256:1479f1bd1c95687d74f6efcd03b658c3f2b419542de1344298fc141fab328e23

Observation 22b0f137-56cf-46b9-8bec-821815d36e17 · outbound

This paper cites Exploring the landscape of distributional robustness for question answering models, 2022.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Exploring the landscape of distributional robustness for question answering models, 2022

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.678715Z

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=2026-08-08T04:53:48.990745Z digest=sha256:9c0a3857c16cad9dd5c3a4293d2a8538567a046c0eaf7d160f3d07a6c32c8446

Observation 1b228548-78de-4f5b-8ca9-7a6afbffc3fd · outbound

This paper cites The effect of natural distribution shift on question answering models.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation The effect of natural distribution shift on question answering models

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.665197Z

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=2026-08-08T04:53:48.994859Z digest=sha256:f5272a5ab34f6a6c2c9179cfedda9acb03cfa25571d01f4025443270ba2ace6b

Observation 973d3343-a8f8-42ec-9622-ad19cca6dec8 · outbound

This paper cites Multi-source unsu- pervised domain adaptation via pseudo target domain.IEEE Transactions on Image Pro- cessing, 31:2122–2135, 2022.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Multi-source unsu- pervised domain adaptation via pseudo target domain.IEEE Transactions on Image Pro- cessing, 31:2122–2135, 2022

Reference 46

Resolution
metadata mismatch
raw_fallback, observed 2026-08-08T04:53:50.040309Z

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=2026-08-08T04:53:48.999199Z digest=sha256:196d701eaf441142031e1a8e357c6f60ac46dfb876d0f128f6dd36a68760d008

Observation aa2a10ab-d799-4a66-aa9d-b8c5177a21da · outbound

This paper cites Curriculum graphco-teachingformulti-targetdomainadaptation.In ProceedingsoftheIEEE/CVFConference on Computer Vision and Pattern Recognition, 2021.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Curriculum graphco-teachingformulti-targetdomainadaptation.In ProceedingsoftheIEEE/CVFConference on Computer Vision and Pattern Recognition, 2021

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.652287Z

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=2026-08-08T04:53:49.003965Z digest=sha256:10520d7c1b43292791c25a606c4f47477ca5dd4474bfa3cef5b5f82cc2664cc5

Observation 8b9b1c00-8955-48ca-b346-3b95016f15ea · outbound

This paper cites Deep domain confusion: Maximizing for domain invariance, 2014.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Deep domain confusion: Maximizing for domain invariance, 2014

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.638630Z

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=2026-08-08T04:53:49.008115Z digest=sha256:8dd4e09793d407213caeffb9ee95df52c62981679fe4fc8c61b60eab627f5b4a

Observation 55606544-2e90-4a48-b3a8-1df7f94268ad · outbound

This paper cites Learningtransferablefeatures with deep adaptation networks.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Learningtransferablefeatures with deep adaptation networks

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.625196Z

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=2026-08-08T04:53:49.012151Z digest=sha256:35ba75b2b11b4d1aa669fff9e7831869336add78371633064515cef45c204487

Observation f98a9477-6e73-4e2d-a9cd-df2771640396 · outbound

This paper cites Domain-adversarial neural networks, 2015.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Domain-adversarial neural networks, 2015

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.611829Z

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=2026-08-08T04:53:49.016712Z digest=sha256:ef36d416d459f4ed29858a41658e9184d46989d0bdc9147c7be0e5ccf749ed8c

Observation 68b4e019-8387-4839-a764-6472e3bca988 · outbound

This paper cites Pseudo-label: Thesimpleandefficientsemi-supervisedlearningmethodfor deep neural networks.ICML 2013 Workshop : Challenges in Representation Learning (WREPL), 07 2013.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Pseudo-label: Thesimpleandefficientsemi-supervisedlearningmethodfor deep neural networks.ICML 2013 Workshop : Challenges in Representation Learning (WREPL), 07 2013

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.598269Z

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=2026-08-08T04:53:49.020957Z digest=sha256:40471f23482ec54b8bda67d27ea6a8a088414ed6f2209ad8078e0ca95384ecfc

Observation af560ac2-4420-465d-8a4c-2e228dcf9bf8 · outbound

This paper cites Structural re-weighting improves graph domain adaptation.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Structural re-weighting improves graph domain adaptation

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.584991Z

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=2026-08-08T04:53:49.025266Z digest=sha256:d896d1109992e04d086aaae0214e8d0dadf11834c72e84c5be4f9a81530e23f2

Observation a1faf9b5-d7a0-4f38-8c3b-c9be82e31d29 · outbound

This paper cites Dane: Domain adaptive networkembedding.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Dane: Domain adaptive networkembedding

Reference 53

Resolution
verified exact
doi, observed 2026-08-08T04:53:49.307109Z

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=2026-08-08T04:53:49.029549Z digest=sha256:99451ab0248f74185173c275957abbe970113e95354f449d790f3e53d35ebfd3

Observation 97b98cf2-1b59-427b-8aad-9ed24c86010c · outbound

This paper cites Unsuperviseddomain adaptive graph convolutional networks.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Unsuperviseddomain adaptive graph convolutional networks

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T04:53:49.033819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.033819Z digest=sha256:0eeb2cb9831d48efca27d7626e0fc1ec7beb5ecbd4b442304d1e09b652a70776

Observation aafec564-75de-4294-8d8c-98aefaa81432 · outbound

This paper cites Shift-robust gnns: Over- coming the limitations of localized graph training data.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Shift-robust gnns: Over- coming the limitations of localized graph training data

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.571636Z

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=2026-08-08T04:53:49.038031Z digest=sha256:1db0b8780c3356e92ec19cf394fe9796aac459e729bce9aa964da00320e12a03

Observation 7a9f4cfd-eba5-4230-982b-d6bc7b674ff7 · outbound

This paper cites Deal: An unsupervised domain adaptive framework for graph-level classification.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Deal: An unsupervised domain adaptive framework for graph-level classification

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Resolution
unresolved
no resolver link, observed 2026-08-08T04:53:49.042268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.042268Z digest=sha256:a25c9c66701bd0337560c64dc6d54af92e204c4e6bc7e416c8df5578ac28e6f5

Observation 782980dd-dbe7-4908-a2f3-70867f197b73 · outbound

This paper cites CoCo: A coupled contrastive framework for unsupervised domain adaptive graph classification.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation CoCo: A coupled contrastive framework for unsupervised domain adaptive graph classification

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.558776Z

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=2026-08-08T04:53:49.046394Z digest=sha256:bc9deae581014865f41db503d4be302747c4a0a2eb91474f642d04e47cf97ac9

Observation 2cece8e3-2f44-4b3c-a71f-ab19ad421c48 · outbound

This paper cites Domain Adaptive Graph Classification.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Domain Adaptive Graph Classification

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-08-08T04:53:49.813220Z

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=2026-08-08T04:53:49.050884Z digest=sha256:30e6cb354b8588665b8dd16767a7516e998987485314dcf92576354444137acf

Observation 6c44a03d-ed27-4097-a0ff-310b5a09e733 · outbound

This paper cites Improving predictive inference under covariate shift by weighting the log-likelihood function.Journal of Statistical Planning and Inference, 90(2):227–244, 2000.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Improving predictive inference under covariate shift by weighting the log-likelihood function.Journal of Statistical Planning and Inference, 90(2):227–244, 2000

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Resolution
unresolved
no resolver link, observed 2026-08-08T04:53:49.055561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.055561Z digest=sha256:55cd001b5c6c9af3168ba29e05619a267c1c85d2dc50a84c442be24f88e19e92

Observation f8139aa1-17cc-4416-8b7b-d167b526bc14 · outbound

This paper cites Fixmatch: Simplifying semi- supervised learning with consistency and confidence.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Fixmatch: Simplifying semi- supervised learning with consistency and confidence

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.545749Z

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=2026-08-08T04:53:49.059969Z digest=sha256:5ac4a460d90c7f46e717704c462da7735621391af316532098c5fcb11a344264

Observation 89f4e070-d403-4a24-be8e-477fe5a45fa8 · outbound

This paper cites Borgwardt.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Borgwardt

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.531989Z

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=2026-08-08T04:53:49.064161Z digest=sha256:19612da0ced6776f0202bd33f0fa627b2fdfbeeb0f5a400e460647b0fd8759d7

Observation 7af67a79-d1e5-4e87-a15f-7de06ad012fa · outbound

This paper cites Bronstein.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Bronstein

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.518294Z

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=2026-08-08T04:53:49.068501Z digest=sha256:9a2046f00a5ec72457abf7de6b129edc085557eed3d1abeb85c8aa0f749338d4

Observation a723f68f-a2a4-4770-bda2-03bc7b8c0774 · outbound

This paper cites Accurate learning of graph representations with graph multiset pooling.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Accurate learning of graph representations with graph multiset pooling

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.505065Z

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=2026-08-08T04:53:49.072771Z digest=sha256:b22f54e5e2f6698df179a20b85ffddfbb7c1eac26313f7f9627a6f52abeeedd4

Observation 7d592332-811a-4cc6-b2d1-91c8b2c80c5f · outbound

This paper cites Toalign: Task- oriented alignment for unsupervised domain adaptation.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Toalign: Task- oriented alignment for unsupervised domain adaptation

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.491484Z

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=2026-08-08T04:53:49.076987Z digest=sha256:fc74c3b650ad69ad9ed85b130b05cbe60e1b5cc0047939b544f81b36595f1984

Observation 80eada65-4fe0-47c6-9317-7e0372c3ba25 · outbound

This paper cites Metaalign: Coordinating do- main alignment and classification for unsupervised domain adaptation.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Metaalign: Coordinating do- main alignment and classification for unsupervised domain adaptation

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.465033Z

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=2026-08-08T04:53:49.087135Z digest=sha256:a704ea78438d803b57a15b8f1737b76c54e383697496785b4fe30d3ee361a8bf

Observation 50af9176-a397-4402-bb6c-1abaa92658f5 · outbound

This paper cites Thenormmustgoon: Dynamic unsupervised domain adaptation by normalization.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Thenormmustgoon: Dynamic unsupervised domain adaptation by normalization

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.451950Z

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=2026-08-08T04:53:49.091340Z digest=sha256:554afb437575dc1d6f5285708be873a219f610ef35a28955ce5ef944b12009d6

Observation 4db63eb6-1359-4e9c-969c-d0f9272d0524 · outbound

This paper cites Statistical inference for high-dimensional matrix-variate factor models.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Statistical inference for high-dimensional matrix-variate factor models

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.438840Z

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=2026-08-08T04:53:49.095373Z digest=sha256:a85621eb92e8e94a170daa46a251864a627e6948717631f85a19e489e78bf604

Observation c6be48ab-44aa-4a12-aefc-d6050e15d67b · outbound

This paper cites On projection robust optimal transport: Sample complexity and model misspecification.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation On projection robust optimal transport: Sample complexity and model misspecification

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.425474Z

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=2026-08-08T04:53:49.100078Z digest=sha256:d9b1c5fd3303aa153e89a38f06cabae5e2000b34b74336c0ccf2c9b778ecfb2c

Observation 0a6293bd-c7bf-4947-a7e3-f33a83304377 · outbound

This paper cites Identification and estimation of threshold matrix-variate factor models.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Identification and estimation of threshold matrix-variate factor models

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.412149Z

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=2026-08-08T04:53:49.104238Z digest=sha256:4e5267307dd834c3065a593d5d028b9d8746000c287023cb9ee6e2ee561aa710

Observation c98f29ef-688e-4ef4-820d-1b4949cf0563 · outbound

This paper cites an unresolved cited work.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Unresolved cited work

Reference 70

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unresolved
raw_fallback, observed 2026-08-08T04:53:50.398518Z

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=2026-08-08T04:53:49.108904Z digest=sha256:3c42615f32cb89daae81c67d23fb060cad53bd4080857f9ca7c784dbd87e0ac0

Observation 9cfb1394-1264-448d-8c7f-02a3346e920c · outbound

This paper cites Time-varyingmatrixfactormodels, 2024.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Time-varyingmatrixfactormodels, 2024

Reference 71

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raw_fallback, observed 2026-08-08T04:53:50.384872Z

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=2026-08-08T04:53:49.113230Z digest=sha256:cae7591dffeda0e5b88c6bb0dae24704451711d6a5862448dd8b04d38c60395b

Observation 6b3154ba-79ac-4552-914e-8ccc2098d65f · outbound

This paper cites Computation of optimal mev in decentralized exchanges.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Computation of optimal mev in decentralized exchanges

Reference 72

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verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.371200Z

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=2026-08-08T04:53:49.117609Z digest=sha256:70adf79c3bdb5b1c5c7b6d73ffd6c59e91b8a6946d015b28b024cf5a9853d3e1

Observation a0691cd3-b612-4322-8192-41422e3ff13a · outbound

This paper cites Mev makes ev- eryonehappyundergreedysequencingrule.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Mev makes ev- eryonehappyundergreedysequencingrule

Reference 73

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raw_fallback, observed 2026-08-08T04:53:50.357404Z

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=2026-08-08T04:53:49.121921Z digest=sha256:fce31d51cac4667c5b1bd9460850045fc736c7ff4e4b5568451e52c23b87ca68

Observation a5143886-758d-4080-b355-ce7d499aad84 · outbound

This paper cites Data-driven knowledge transfer in batchQ∗ learning.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Data-driven knowledge transfer in batchQ∗ learning

Reference 74

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raw_fallback, observed 2026-08-08T04:53:49.791964Z

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=2026-08-08T04:53:49.126153Z digest=sha256:45d23ac80e082ab6ec9ba34d9f9ce39b4ebfbee6f0fb70e48b16181a96c44413

Observation fda8ea5a-91a3-4860-acfe-f0b35fc35e84 · outbound

This paper cites Dynamic Contextual Pricing with Doubly Non-Parametric Random Utility Models.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Dynamic Contextual Pricing with Doubly Non-Parametric Random Utility Models

Reference 75

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no resolver link, observed 2026-08-08T04:53:49.130114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.130114Z digest=sha256:712ed961a8ca929935dfc9780e8a409430341f35fcceb0d88ed728790a8dce40

Observation 6c5cd544-6e3e-4727-b8ca-696985b4dfc7 · outbound

This paper cites Community network auto-regression for high- dimensional time series.Journal of Econometrics, 235(2):1239–1256, 2023.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Community network auto-regression for high- dimensional time series.Journal of Econometrics, 235(2):1239–1256, 2023

Reference 76

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raw_fallback, observed 2026-08-08T04:53:50.344038Z

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=2026-08-08T04:53:49.134500Z digest=sha256:081f7d9aedd8cf45332a7c410e8f6a4a3b0eb448a0ec0535d1ebdf02dde129b5

Observation b649e392-e86b-435f-9507-e5693515a0e8 · outbound

This paper cites Constrained factor models for high-dimensional matrix-variate time series.Journal of the American Statistical Association, 2019.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Constrained factor models for high-dimensional matrix-variate time series.Journal of the American Statistical Association, 2019

Reference 77

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raw_fallback, observed 2026-08-08T04:53:50.330651Z

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=2026-08-08T04:53:49.138480Z digest=sha256:3ec3da2c7d77f4cd9d639ba9baa7bee0d0c4e832192b976f05607fddd2d79330

Observation febfdd5b-8a2a-4cc5-92ac-e1e0d8b5927e · outbound

This paper cites Modeling Multivariate Spatial-Temporal Data with Latent Low-Dimensional Dynamics.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Modeling Multivariate Spatial-Temporal Data with Latent Low-Dimensional Dynamics

Reference 78

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no resolver link, observed 2026-08-08T04:53:49.142542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.142542Z digest=sha256:f85b598638df31460260f50f61f241898ef89d937970b680ac17628c566cecab

Observation bc1976e1-ebcf-4485-937a-4308bddf800c · outbound

This paper cites Modeling dynamic transport network with matrix factor models: with an application to international trade flow.Journal of Data Science, 2022.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Modeling dynamic transport network with matrix factor models: with an application to international trade flow.Journal of Data Science, 2022

Reference 79

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raw_fallback, observed 2026-08-08T04:53:50.316878Z

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=2026-08-08T04:53:49.147151Z digest=sha256:599dd094ae58801261f705eaeb1d01826263fae5515b7e4d6c1c1c2cb9ea86fb

Observation 8f40dbbf-b745-466c-a00a-088b13ca0045 · outbound

This paper cites Transfer q-learning.arXiv preprint arXiv:2202.04709, 2022.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Transfer q-learning.arXiv preprint arXiv:2202.04709, 2022

Reference 80

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raw_fallback, observed 2026-08-08T04:53:49.682890Z

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=2026-08-08T04:53:49.151081Z digest=sha256:ec4a8a7ba6ca2a89870066bdec19ec2c5b633dd965dd982e02e56d0075e86c2f

Observation 2af58e38-4889-4e29-9d79-9af24df6d6e1 · outbound

This paper cites Reinforcement learning in latent heterogeneous environments.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Reinforcement learning in latent heterogeneous environments

Reference 81

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raw_fallback, observed 2026-08-08T04:53:50.303195Z

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=2026-08-08T04:53:49.155669Z digest=sha256:154bef30ec6145aa7e9d26632aab578ed619bbd8fe3ca548e350845c8c83e25d

Observation 2d607b76-ee69-46a9-8b18-80991b764ba0 · outbound

This paper cites Distributed Tensor Principal Component Analysis with Data Heterogeneity.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Distributed Tensor Principal Component Analysis with Data Heterogeneity

Reference 82

Resolution
verified exact
local_arxiv, observed 2026-08-08T04:53:49.600958Z

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=2026-08-08T04:53:49.159884Z digest=sha256:65544146ff3287de2637fd5f7c7b5d3b4d5a50974480d48e97ca915f5e4e7614

Observation 56f5f2bb-6ab3-4075-8417-664da25aedd1 · outbound

This paper cites Advancing Information Integration through Empirical Likelihood: Selective Reviews and a New Idea.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Advancing Information Integration through Empirical Likelihood: Selective Reviews and a New Idea

Reference 83

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no resolver link, observed 2026-08-08T04:53:49.164616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.164616Z digest=sha256:4af1573f974fefad831f43d2b89544fa233d1dbaff3163314605dab8d62f3398

Observation c3d54bc8-231c-49d3-9e68-064fb9e22c05 · outbound

This paper cites High-Dimensional Tensor Classification with CP Low-Rank Discriminant Structure.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation High-Dimensional Tensor Classification with CP Low-Rank Discriminant Structure

Reference 84

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no resolver link, observed 2026-08-08T04:53:49.169032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.169032Z digest=sha256:2ef9daf4e0f41e906c27145790c4a218d625223a4e861a6a818f03f97be8aaa6

Observation f80ebf38-412d-4800-878b-351c59db7ea8 · outbound

This paper cites High-Dimensional Tensor Discriminant Analysis with Incomplete Tensors.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation High-Dimensional Tensor Discriminant Analysis with Incomplete Tensors

Reference 85

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no resolver link, observed 2026-08-08T04:53:49.173610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.173610Z digest=sha256:d9837de1b3aab34c6b31c8ee0da893e818eebbc3ad8b521b430eb27fb85c4eda

Observation 8aace5d3-c52f-47bf-b510-c70429c78117 · outbound

This paper cites Stochastic linear bandits with latent hetero- geneity.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Stochastic linear bandits with latent hetero- geneity

Reference 86

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no resolver link, observed 2026-08-08T04:53:49.178081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.178081Z digest=sha256:fa73ca743e8e576256866bade95347fcc9a5fc2bd7993f11223b87ac5509a83f

Observation 6395d05c-ec72-48d5-a31e-892144c5493e · outbound

This paper cites Statistical Inference for Low-Rank Tensor Models.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Statistical Inference for Low-Rank Tensor Models

Reference 87

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no resolver link, observed 2026-08-08T04:53:49.182442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.182442Z digest=sha256:b914fecbae259e8bc6858b0ebd2aad8069696f37459528df6cb3af48b9e5fc69

Observation 07e6cd61-95bb-4af7-b7d9-b02b8812c3e3 · outbound

This paper cites On the expressive power of deep learning: A tensor analysis.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation On the expressive power of deep learning: A tensor analysis

Reference 88

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raw_fallback, observed 2026-08-08T04:53:50.290170Z

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=2026-08-08T04:53:49.186974Z digest=sha256:d9c17ae4e52a128fb91f74b8d6285872e795dbe957f1c2fdd496acbca007e9de

Observation 0df12790-43f5-4726-a7ca-8ac41cf2cdfc · outbound

This paper cites Tensor contraction layers for parsimonious deep nets.CVPR, pages 1940–1946, 2017.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Tensor contraction layers for parsimonious deep nets.CVPR, pages 1940–1946, 2017

Reference 89

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raw_fallback, observed 2026-08-08T04:53:50.276540Z

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=2026-08-08T04:53:49.191348Z digest=sha256:f741b0b059a85538b27f399d279ab9d28c6475a40af71fd84dffd91cafaf4f47

Observation c96064e2-400c-4ed4-9269-9a891b862886 · outbound

This paper cites Lipton, Arinbjorn Kolbeinsson, Aran Khanna, Tommaso Furlanello, and Anima Anandkumar.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Lipton, Arinbjorn Kolbeinsson, Aran Khanna, Tommaso Furlanello, and Anima Anandkumar

Reference 90

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raw_fallback, observed 2026-08-08T04:53:50.262803Z

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=2026-08-08T04:53:49.195685Z digest=sha256:c3051c538b7206873afe1bd7f90784033f611d04eb21b76920ca5ae4d8ac31cb

Observation d2d01238-04ba-453f-9281-a08722e007b0 · outbound

This paper cites Graph Tensor Networks: An Intuitive Framework for Designing Large-Scale Neural Learning Systems on Multiple Domains.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Graph Tensor Networks: An Intuitive Framework for Designing Large-Scale Neural Learning Systems on Multiple Domains

Reference 91

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verified exact
local_arxiv, observed 2026-08-08T04:53:49.409765Z

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=2026-08-08T04:53:49.199910Z digest=sha256:16d70656d5f69d07d2715a315d592e30cd3d34c573e297aa6f302146fc23f558

Observation 0669f980-c788-4a41-b621-bd2879b72a05 · outbound

This paper cites Tensor-view topological graph neural network.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Tensor-view topological graph neural network

Reference 92

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verified fuzzy
raw_fallback, observed 2026-08-08T04:53:50.248251Z

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=2026-08-08T04:53:49.204348Z digest=sha256:e99a352b56093df63730e458f1c863158e76fd9ba8829f0e9c6115c5568ef1bb

Observation 4d26a0b7-b320-4f45-ae1a-e0ef4a6528e2 · outbound

This paper cites Tensor-Fused Multi-View Graph Contrastive Learning.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Tensor-Fused Multi-View Graph Contrastive Learning

Reference 93

Resolution
verified exact
local_arxiv, observed 2026-08-08T04:53:49.389550Z

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=2026-08-08T04:53:49.208621Z digest=sha256:fd3fcee3f9ea6b1648985341794b28010cc4740a23e3c751b4b6b23dafb8da22

Observation a8f870c1-e8be-4a9d-8cdf-ebcb2c2e44c8 · outbound

This paper cites Conditional prediction roc bands for graph classification.AISTATS, 2025, Mai Khao, Thailand, 2024.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Conditional prediction roc bands for graph classification.AISTATS, 2025, Mai Khao, Thailand, 2024

Reference 94

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raw_fallback, observed 2026-08-08T04:53:50.234662Z

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=2026-08-08T04:53:49.213084Z digest=sha256:1672fd6a48af4bbb428f3998be8fe9b8529c740a4a3ecb6574597110a71b5302

Observation 0f813711-fb19-4609-b854-0c26df473dfc · outbound

This paper cites Conditional Uncertainty Quantification for Tensorized Topological Neural Networks.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Conditional Uncertainty Quantification for Tensorized Topological Neural Networks

Reference 95

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no resolver link, observed 2026-08-08T04:53:49.217375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.217375Z digest=sha256:16a3acc9583be3f0a1aaaa60fa7a22d247a8d276ee1922b53a4973f06bd2e2c6

Observation 610aff8d-0e37-4ec6-9937-2f3981995292 · outbound

This paper cites TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting

Reference 96

Resolution
verified exact
local_arxiv, observed 2026-08-08T04:53:49.356522Z

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=2026-08-08T04:53:49.221716Z digest=sha256:eaf8c4fda706490eb4b2813345f0703b812b2c8bbb9bf17d729810470e520dca

Observation 852d24cf-9147-41ec-a9b7-bd52c70a8bdb · outbound

This paper cites Persistence images: A stable vector representation of persistent homology.Journal of Machine Learning Research, 18, 2017.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Persistence images: A stable vector representation of persistent homology.Journal of Machine Learning Research, 18, 2017

Reference 97

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raw_fallback, observed 2026-08-08T04:53:50.220212Z

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=2026-08-08T04:53:49.226606Z digest=sha256:0fe91551982e6e258251f30ad2359af4754b0f880cc3a1bbfe63b1ebf91b7ea7

Observation 1617af4b-b713-4e34-bf1b-c85f25e2cbe5 · outbound

This paper cites Derivation and validation of toxicophores for mutagenicity prediction.J.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Derivation and validation of toxicophores for mutagenicity prediction.J

Reference 98

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raw_fallback, observed 2026-08-08T04:53:50.205114Z

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=2026-08-08T04:53:49.230673Z digest=sha256:3d8eb85cc2c1c0856d71ac71912acbb548413026a176dca352d155cd689726bc

Observation 723d2f6f-75b4-4172-b704-01ba9bbd17ff · outbound

This paper cites Dobson and Andrew J.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Dobson and Andrew J

Reference 99

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no resolver link, observed 2026-08-08T04:53:49.234828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:53:49.234828Z digest=sha256:43d8f34a843a08057a0fdb1ef5eddcebfb431cad552d3ae4bfaa0e45f085247c

Observation 7a904a4d-0b8a-4776-9c99-7256857385c8 · outbound

This paper cites Spline-Fitting with a genetic algorithm: A method for developing classification {Structure–Activity} relationships.J.

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Spline-Fitting with a genetic algorithm: A method for developing classification {Structure–Activity} relationships.J

Reference 100

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raw_fallback, observed 2026-08-08T04:53:50.191452Z

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=2026-08-08T04:53:49.239186Z digest=sha256:0cfc7a5fb6d6edafed9c1d0ee1d10bfb79d8607f90efd11bc6da70fdb9c202a0

Pith citing papers

No inbound Pith citation observations are available.