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

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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

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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

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

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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

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

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

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

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

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

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

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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

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

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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

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

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

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

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

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

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

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

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

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

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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

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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

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

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

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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

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

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

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

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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 2026-08-09T06:31:02.800959+00:00.

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.

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

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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 2026-08-09T06:31:02.800959+00:00.

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.

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 2026-08-09T06:31:02.800959+00:00.

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

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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 2026-08-09T06:31:02.800959+00:00.

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.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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

Reference 67

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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

Reference 69

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 2026-08-09T06:31:02.800959+00:00.

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

Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

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Resolution: verified fuzzy; 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 2026-08-09T06:31:02.800959+00:00.

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

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Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

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Resolution: verified fuzzy; 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 2026-08-09T06:31:02.800959+00:00.

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

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Resolution: verified exact; 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 2026-08-09T06:31:02.800959+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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Resolution: verified fuzzy; 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 2026-08-09T06:31:02.800959+00:00.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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Resolution: verified fuzzy; 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 2026-08-09T06:31:02.800959+00:00.

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

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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 2026-08-09T06:31:02.800959+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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Resolution: verified fuzzy; 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 2026-08-09T06:31:02.800959+00:00.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

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Resolution: 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 2026-08-09T06:31:02.800959+00:00.

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

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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 2026-08-09T06:31:02.800959+00:00.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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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 2026-08-09T06:31:02.800959+00:00.

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

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Resolution: verified fuzzy; 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 2026-08-09T06:31:02.800959+00:00.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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