Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge | Paper Citation Record

Observation 8e0a5333-5bcd-440d-9972-63a93ea937e6 · outbound

This paper cites Modeling polypharmacy side effects with graph convolutional networks.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Modeling polypharmacy side effects with graph convolutional networks

Reference 1

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Observation 0e11f0a5-626d-4f60-8c46-86e506263a78 · outbound

This paper cites Graph neural networks for social recommendation, 2019.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Graph neural networks for social recommendation, 2019

Reference 2

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This paper cites Neural relational inference for interacting systems, 2018.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Neural relational inference for interacting systems, 2018

Reference 3

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Observation 9ff98b02-fdb6-473b-be27-6536fdc2540f · outbound

This paper cites Variational Graph Auto-Encoders.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Variational Graph Auto-Encoders

Reference 4

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Observation b0df454f-2065-4374-aaa7-d95d431a6870 · outbound

This paper cites NED-GNN: Detecting and Dropping Noisy Edges in Graph Neural Networks , pages 91–105.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge NED-GNN: Detecting and Dropping Noisy Edges in Graph Neural Networks , pages 91–105

Reference 5

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Observation a08bb3c5-f432-4d25-83df-4a704f0a4a9b · outbound

This paper cites Towards robust graph neural networks for noisy graphs with sparse labels, 2022.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Towards robust graph neural networks for noisy graphs with sparse labels, 2022

Reference 6

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Observation 70cc5c8c-4b64-4b44-92c2-75f7f8913ef5 · outbound

This paper cites Lichtenwalter, and Nitesh V.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Lichtenwalter, and Nitesh V

Reference 7

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Observation 8a2ff665-d99b-45e7-90f7-7ed92d4bfb0b · outbound

This paper cites Evaluating graph neural networks for link prediction: Current pitfalls and new benchmarking, 2023.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Evaluating graph neural networks for link prediction: Current pitfalls and new benchmarking, 2023

Reference 8

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Observation 3eaac702-cc95-4999-b193-7e20567b4836 · outbound

This paper cites Graph convolution for semi- supervised classification: Improved linear separability and out-of-distribution generalization, 2022.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Graph convolution for semi- supervised classification: Improved linear separability and out-of-distribution generalization, 2022

Reference 9

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This paper cites Uncovering disease-disease relationships through the incomplete interactome.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Uncovering disease-disease relationships through the incomplete interactome

Reference 10

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Observation f108c2d0-d49b-4df2-87fe-23c606db54b8 · outbound

This paper cites Ned-gnn: Detecting and dropping noisy edges in graph neural networks.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Ned-gnn: Detecting and dropping noisy edges in graph neural networks

Reference 11

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Observation 2e2606ab-530b-4e41-ac49-389a7d7f2e9d · outbound

This paper cites Adver- sarial examples on graph data: Deep insights into attack and defense, 2019.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Adver- sarial examples on graph data: Deep insights into attack and defense, 2019

Reference 12

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Observation 50aaebdc-afa9-42ac-a25b-3e5c9034dfc2 · outbound

This paper cites Garnet: Reduced-rank topology learning for robust and scalable graph neural networks.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Garnet: Reduced-rank topology learning for robust and scalable graph neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:31.657007Z

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Observation 78115f93-b4a6-40f2-b95f-ec3aded78c9e · outbound

This paper cites All you need is low (rank) defending against adversarial attacks on graphs.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge All you need is low (rank) defending against adversarial attacks on graphs

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:31.355980Z

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This paper cites Elastic graph neural networks.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Elastic graph neural networks

Reference 15

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Observation 3f215b61-4852-4b4c-871b-9d838edcdfaa · outbound

This paper cites Gnnguard: Defending graph neural networks against adversarial attacks.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Gnnguard: Defending graph neural networks against adversarial attacks

Reference 16

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Observation e3a4f79d-caa5-4e47-afa3-a495015c1cfc · outbound

This paper cites Adversarial Examples on Graph Data: Deep Insights into Attack and Defense.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Adversarial Examples on Graph Data: Deep Insights into Attack and Defense

Reference 17

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Observation c3f9edc2-4ef1-4308-90b0-ab36b260f94a · outbound

This paper cites GraphDefense: Towards Robust Graph Convolutional Networks.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge GraphDefense: Towards Robust Graph Convolutional Networks

Reference 18

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Observation f954aa37-de91-4e9d-af3d-38be6d007e47 · outbound

This paper cites Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective

Reference 19

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Observation 99d78a0c-7de7-48a6-a4ba-dc80296e53eb · outbound

This paper cites Graph structure learning for robust graph neural networks, 2020.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Graph structure learning for robust graph neural networks, 2020

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:30.550313Z

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Observation c877f683-255e-4b6f-b8f8-b8e8d0e23de7 · outbound

This paper cites Transferring robustness for graph neural network against poisoning attacks.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Transferring robustness for graph neural network against poisoning attacks

Reference 21

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Observation 3efc1132-cba5-4ece-9698-583e33a2f534 · outbound

This paper cites Variational inference for graph convolutional networks in the absence of graph data and adversarial settings.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Variational inference for graph convolutional networks in the absence of graph data and adversarial settings

Reference 22

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Observation f8dd4ad8-3194-4336-8fb6-02556d23bd6b · outbound

This paper cites Robustness of graph neural networks at scale.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Robustness of graph neural networks at scale

Reference 23

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Observation 89be55b8-d5b6-43ec-a0ac-0cc891ac4525 · outbound

This paper cites Graph attention networks, 2018.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Graph attention networks, 2018

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:29.357310Z

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Observation 2bbc30ab-5ac3-4b49-964b-78c7fa4be678 · outbound

This paper cites How powerful are graph neural networks?, 2019.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge How powerful are graph neural networks?, 2019

Reference 25

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This paper cites Collective classification in network data.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Collective classification in network data

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:29.079439Z

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Observation 0053fce2-47c7-434a-9c21-d6bb4260e87c · outbound

This paper cites Kingma and Jimmy Ba.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Kingma and Jimmy Ba

Reference 27

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This paper cites Graph Attention Networks.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Graph Attention Networks

Reference 28

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This paper cites Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling

Reference 29

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This paper cites Heterogeneous graph transformer, 2020.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Heterogeneous graph transformer, 2020

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:28.763052Z

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Observation c43e7e13-f167-439f-af31-3a5dd07b2a23 · outbound

This paper cites Kegg: kyoto encyclopedia of genes and genomes.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Kegg: kyoto encyclopedia of genes and genomes

Reference 31

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This paper cites Proteinbert: a universal deep-learning model of protein sequence and function.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Proteinbert: a universal deep-learning model of protein sequence and function

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:28.217571Z

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This paper cites Rdkit: A software suite for cheminformatics, computational chemistry, and predictive modeling.[google scholar].

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Rdkit: A software suite for cheminformatics, computational chemistry, and predictive modeling.[google scholar]

Reference 33

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Observation a3d2678c-459d-462a-a77b-eee0ba51dae2 · outbound

This paper cites Lu, Kevin K.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Lu, Kevin K

Reference 34

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Observation 427e3dbf-3fd2-4d8e-9519-38fa218ac8b2 · outbound

This paper cites Mpi-vgae: protein–metabolite enzymatic reaction link learning by variational graph autoencoders.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Mpi-vgae: protein–metabolite enzymatic reaction link learning by variational graph autoencoders

Reference 35

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Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 36

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Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 37

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This paper cites Limitations.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Limitations

Reference 38

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This paper cites • All the theorems, formulas, and proofs in the paper should be numbered and cross- referenced.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge • All the theorems, formulas, and proofs in the paper should be numbered and cross- referenced

Reference 39

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Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 40

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This paper cites The main page of the repository contains a detailed instruction to replicate all results in this paper.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge The main page of the repository contains a detailed instruction to replicate all results in this paper

Reference 41

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Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 42

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This paper cites We explicitly state that each hyper-parameter configuration is run with 10 different random initializations on a fixed node splits.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge We explicitly state that each hyper-parameter configuration is run with 10 different random initializations on a fixed node splits

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:25.112012Z

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Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 44

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This paper cites • If the authors answer No, they should explain the special circumstances that require a deviation from the Code of Ethics.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge • If the authors answer No, they should explain the special circumstances that require a deviation from the Code of Ethics

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:24.536895Z

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This paper cites And we also include a potential negative societal impact in the appendix.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge And we also include a potential negative societal impact in the appendix

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:24.350683Z

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Observation e5d6e412-16e8-40df-a86c-5306816cb4aa · outbound

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Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 47

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This paper cites • The authors should cite the original paper that produced the code package or dataset.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge • The authors should cite the original paper that produced the code package or dataset

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:24.177136Z

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

Observation 161e2553-5a89-4e7a-b0b2-9152802ad8fd · outbound

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Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:28:24.037170Z

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

Observation 3f2cf1f5-be06-474d-89cf-d97035dc8f0b · outbound

This paper cites an unresolved cited work.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 50

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Observation df3cf290-f067-408e-ac10-3115a37c040a · outbound

This paper cites • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:28:23.603409Z

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Observation 353be3a1-d034-4c37-bdac-d095abb81a5e · outbound

This paper cites an unresolved cited work.

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:28:23.364744Z

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

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