Graph Counterfactual Explainable AI via Latent Space Traversal | Paper Citation Record

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This paper cites A permutation testing framework to compare groups of brain networks.

Graph Counterfactual Explainable AI via Latent Space Traversal A permutation testing framework to compare groups of brain networks

Reference 1

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Observation d94c1b4f-8c6c-441d-bf19-4893982d7a24 · outbound

This paper cites Nonparametric bayes mod- eling of populations of networks.

Graph Counterfactual Explainable AI via Latent Space Traversal Nonparametric bayes mod- eling of populations of networks

Reference 2

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Observation ac875e9d-91fc-4055-8ce9-c8d19aee4cab · outbound

This paper cites Graph alignment exploiting the spatial organization improves the similarity of brain networks.

Graph Counterfactual Explainable AI via Latent Space Traversal Graph alignment exploiting the spatial organization improves the similarity of brain networks

Reference 3

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Observation 5bc41a1d-39b7-4ba9-ab02-ac2c64349d4e · outbound

This paper cites Statistical shape analysis of brain arterial networks (BAN).

Graph Counterfactual Explainable AI via Latent Space Traversal Statistical shape analysis of brain arterial networks (BAN)

Reference 4

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This paper cites an unresolved cited work.

Graph Counterfactual Explainable AI via Latent Space Traversal Unresolved cited work

Reference 5

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Observation 9874953f-02de-4bbb-8335-7683755c8876 · outbound

This paper cites Tree-space statistics and approximations for large-scale analysis of anatomical trees.

Graph Counterfactual Explainable AI via Latent Space Traversal Tree-space statistics and approximations for large-scale analysis of anatomical trees

Reference 6

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Observation 3761a09c-9e0d-4d7c-a53f-87e2bc9791e7 · outbound

This paper cites Public transport networks: em- pirical analysis and modeling.

Graph Counterfactual Explainable AI via Latent Space Traversal Public transport networks: em- pirical analysis and modeling

Reference 7

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Observation 3b7a9707-511c-4b56-888b-ed290797dd62 · outbound

This paper cites Interpreting Equivariant Representations.

Graph Counterfactual Explainable AI via Latent Space Traversal Interpreting Equivariant Representations

Reference 8

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Observation b35b1556-965a-403a-b3fd-68522e6831b1 · outbound

This paper cites Beyond trivial counterfactual explanations with diverse valu- able explanations.

Graph Counterfactual Explainable AI via Latent Space Traversal Beyond trivial counterfactual explanations with diverse valu- able explanations

Reference 9

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Observation 532efe47-9230-4c57-ab38-2365f8e7ab1f · outbound

This paper cites Learning model-agnostic coun- terfactual explanations for tabular data.

Graph Counterfactual Explainable AI via Latent Space Traversal Learning model-agnostic coun- terfactual explanations for tabular data

Reference 10

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Observation f1b00e43-d9de-4e40-8424-344e44d78806 · outbound

This paper cites Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review.

Graph Counterfactual Explainable AI via Latent Space Traversal Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review

Reference 11

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Observation c37338a4-4737-4677-8c92-38da200cf134 · outbound

This paper cites Gnnx-bench: Unravelling the utility of perturbation-based gnn explain- ers through in-depth benchmarking.

Graph Counterfactual Explainable AI via Latent Space Traversal Gnnx-bench: Unravelling the utility of perturbation-based gnn explain- ers through in-depth benchmarking

Reference 12

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Observation 78b1af7e-c629-48ae-879b-6b4af9075e8f · outbound

This paper cites A survey on graph counterfactual explanations: defini- tions, methods, evaluation, and research chal- lenges.

Graph Counterfactual Explainable AI via Latent Space Traversal A survey on graph counterfactual explanations: defini- tions, methods, evaluation, and research chal- lenges

Reference 13

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Observation 7591a18f-705b-4a26-80c2-e3b5fdc608d1 · outbound

This paper cites Local Rule-Based Explanations of Black Box Decision Systems.

Graph Counterfactual Explainable AI via Latent Space Traversal Local Rule-Based Explanations of Black Box Decision Systems

Reference 14

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Observation d6ccc787-9cc1-40e6-9b8c-82b2379c59b8 · outbound

This paper cites Multi-objective coun- terfactual explanations.

Graph Counterfactual Explainable AI via Latent Space Traversal Multi-objective coun- terfactual explanations

Reference 15

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Observation faca6414-7c02-4b46-a62c-aecc7f5ff184 · outbound

This paper cites Actionable recourse in linear classification.

Graph Counterfactual Explainable AI via Latent Space Traversal Actionable recourse in linear classification

Reference 16

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Observation 58801f80-a7cc-4de8-9250-37a8772f35d9 · outbound

This paper cites Face: feasible and actionable counterfactual expla- nations.

Graph Counterfactual Explainable AI via Latent Space Traversal Face: feasible and actionable counterfactual expla- nations

Reference 17

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Observation bc9129b0-79cd-491b-ab41-bec888b87115 · outbound

This paper cites Efficient search for diverse co- herent explanations.

Graph Counterfactual Explainable AI via Latent Space Traversal Efficient search for diverse co- herent explanations

Reference 18

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Observation 95ae3334-2a15-4d6a-b3f8-cb919f935b5e · outbound

This paper cites Explaining machine learning classifiers through diverse counterfactual expla- nations.

Graph Counterfactual Explainable AI via Latent Space Traversal Explaining machine learning classifiers through diverse counterfactual expla- nations

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.583992Z

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Observation 7035ebf1-5ffe-4992-b97c-f83d9f06df88 · outbound

This paper cites Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers.

Graph Counterfactual Explainable AI via Latent Space Traversal Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers

Reference 20

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Observation 3c33ff41-b30b-44d7-b84b-8886b5f4aff6 · outbound

This paper cites Algo- rithmic recourse under imperfect causal knowl- edge: a probabilistic approach.

Graph Counterfactual Explainable AI via Latent Space Traversal Algo- rithmic recourse under imperfect causal knowl- edge: a probabilistic approach

Reference 21

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Observation e778e1c8-e5d4-430c-839e-0739b879af26 · outbound

This paper cites Explanations based on the missing: Towards contrastive ex- planations with pertinent negatives.

Graph Counterfactual Explainable AI via Latent Space Traversal Explanations based on the missing: Towards contrastive ex- planations with pertinent negatives

Reference 22

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Observation 31d52d62-0fc0-4285-a7a3-616ecffeb98c · outbound

This paper cites Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems.

Graph Counterfactual Explainable AI via Latent Space Traversal Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems

Reference 23

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Observation 466a23bc-eb49-4037-833a-6d4bce8deb2b · outbound

This paper cites Counterfactual Explanations via Riemannian Latent Space Traversal.

Graph Counterfactual Explainable AI via Latent Space Traversal Counterfactual Explanations via Riemannian Latent Space Traversal

Reference 24

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Observation 407e845d-9c7d-407c-98da-d8852a6b7e10 · outbound

This paper cites Diffeomorphic explanations with normalizing flows.

Graph Counterfactual Explainable AI via Latent Space Traversal Diffeomorphic explanations with normalizing flows

Reference 25

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Observation 9e11a399-e333-483b-980d-dd8399c3eb47 · outbound

This paper cites Ceflow: A robust and efficient counterfactual ex- planation framework for tabular data using nor- malizing flows.

Graph Counterfactual Explainable AI via Latent Space Traversal Ceflow: A robust and efficient counterfactual ex- planation framework for tabular data using nor- malizing flows

Reference 26

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Observation cbabe93a-87ac-49c1-b80d-593226d8b753 · outbound

This paper cites Diffusion models for counterfactual expla- nations.

Graph Counterfactual Explainable AI via Latent Space Traversal Diffusion models for counterfactual expla- nations

Reference 27

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Observation e92f04a6-6f27-466e-8b4e-20aac7a4fcfb · outbound

This paper cites Fast diffusion-based counterfactuals for shortcut re- moval and generation.

Graph Counterfactual Explainable AI via Latent Space Traversal Fast diffusion-based counterfactuals for shortcut re- moval and generation

Reference 28

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Observation 6f9f7dc1-6f48-4047-8bc4-9a34a04388a8 · outbound

This paper cites Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment.

Graph Counterfactual Explainable AI via Latent Space Traversal Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment

Reference 29

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Observation e32b77f8-9225-4686-afd1-886af8a956e9 · outbound

This paper cites Global counterfactual explainer for graph neural networks.

Graph Counterfactual Explainable AI via Latent Space Traversal Global counterfactual explainer for graph neural networks

Reference 30

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Observation 1dc46238-5b0c-46e8-88e0-dfd6feac9102 · outbound

This paper cites D4explainer: In-distribution ex- planations of graph neural network via dis- crete denoising diffusion.

Graph Counterfactual Explainable AI via Latent Space Traversal D4explainer: In-distribution ex- planations of graph neural network via dis- crete denoising diffusion

Reference 31

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Observation 83b542c9-0482-4e9d-9578-b3b5473d4e3c · outbound

This paper cites Robust counterfactual explana- tions on graph neural networks.

Graph Counterfactual Explainable AI via Latent Space Traversal Robust counterfactual explana- tions on graph neural networks

Reference 32

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Observation 1851b3eb-1502-4566-915e-3f6d6125e23d · outbound

This paper cites Clear: Gen- erative counterfactual explanations on graphs.

Graph Counterfactual Explainable AI via Latent Space Traversal Clear: Gen- erative counterfactual explanations on graphs

Reference 33

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Observation 30966ae6-2081-4f47-957e-24168c5a00c3 · outbound

This paper cites GraphV AE: Towards generation of small graphs using variational autoencoders.

Graph Counterfactual Explainable AI via Latent Space Traversal GraphV AE: Towards generation of small graphs using variational autoencoders

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.451500Z

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Observation 3f92a47b-53b7-465b-98f3-f1fa0f256ef3 · outbound

This paper cites Auto- Encoding variational bayes.

Graph Counterfactual Explainable AI via Latent Space Traversal Auto- Encoding variational bayes

Reference 35

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Observation 3dfdd241-1d4b-46d2-915e-1abab8797cf9 · outbound

This paper cites Variational graph Auto-Encoders.

Graph Counterfactual Explainable AI via Latent Space Traversal Variational graph Auto-Encoders

Reference 36

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Observation 6351f764-f0ae-413e-9e01-0d2e774de442 · outbound

This paper cites On the universality of invariant networks.

Graph Counterfactual Explainable AI via Latent Space Traversal On the universality of invariant networks

Reference 37

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Observation d67a341e-bd8f-4512-a0e2-e12679aa3b08 · outbound

This paper cites Permutation equivariant layers for higher order interactions.

Graph Counterfactual Explainable AI via Latent Space Traversal Permutation equivariant layers for higher order interactions

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.398683Z

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This paper cites Invariant and equivariant graph networks.

Graph Counterfactual Explainable AI via Latent Space Traversal Invariant and equivariant graph networks

Reference 39

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This paper cites Multiresolution Equivariant Graph Variational Autoencoder.

Graph Counterfactual Explainable AI via Latent Space Traversal Multiresolution Equivariant Graph Variational Autoencoder

Reference 40

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Observation b4ad1e6d-4348-4ec5-b73d-dd167d7ebf52 · outbound

This paper cites Geometric deep learning: Grids, groups, graphs, geodesics, and gauges.

Graph Counterfactual Explainable AI via Latent Space Traversal Geometric deep learning: Grids, groups, graphs, geodesics, and gauges

Reference 41

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Observation dd3506b6-033e-417f-862d-0eda820ef0ec · outbound

This paper cites The general theory of permutation equivarant neural networks and higher order graph variational encoders.

Graph Counterfactual Explainable AI via Latent Space Traversal The general theory of permutation equivarant neural networks and higher order graph variational encoders

Reference 42

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Observation f6e2d154-86a5-4784-97da-2bdca16e0601 · outbound

This paper cites beta-vae: Learning basic visual concepts with a constrained variational framework.

Graph Counterfactual Explainable AI via Latent Space Traversal beta-vae: Learning basic visual concepts with a constrained variational framework

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.366692Z

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Observation a0bddbe5-68f6-46e1-a5af-332f0d368172 · outbound

This paper cites Categorical reparameterization with gumbel- softmax.

Graph Counterfactual Explainable AI via Latent Space Traversal Categorical reparameterization with gumbel- softmax

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.354208Z

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Observation 89a77634-848f-4a87-ab1f-e79269d18fb8 · outbound

This paper cites Comparison of descriptor spaces for chemical compound retrieval and classification.

Graph Counterfactual Explainable AI via Latent Space Traversal Comparison of descriptor spaces for chemical compound retrieval and classification

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.340386Z

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Observation 935dd28c-8c27-41f0-95c5-dc26646ed495 · outbound

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

Graph Counterfactual Explainable AI via Latent Space Traversal Derivation and validation of toxicophores for mutagenicity prediction

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.327764Z

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Observation e496a4e6-092e-4f14-a336-ce4f87c1250b · outbound

This paper cites Iam graph database repository for graph based pattern recognition and machine learning.

Graph Counterfactual Explainable AI via Latent Space Traversal Iam graph database repository for graph based pattern recognition and machine learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.314834Z

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Observation 03e35464-78d7-4393-80a8-171310b01354 · outbound

This paper cites Understanding Isomorphism Bias in Graph Data Sets.

Graph Counterfactual Explainable AI via Latent Space Traversal Understanding Isomorphism Bias in Graph Data Sets

Reference 48

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Observation c0d1e392-8fc6-4f1a-be6b-ca348cfd73d1 · outbound

This paper cites Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, and Marion Neumann.

Graph Counterfactual Explainable AI via Latent Space Traversal Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, and Marion Neumann

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.301762Z

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Observation 3ccc8bb1-c5e3-4ff5-97ca-3a42d4fecd41 · outbound

This paper cites Global counterfactual explainer for graph neural networks.

Graph Counterfactual Explainable AI via Latent Space Traversal Global counterfactual explainer for graph neural networks

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:20:18.289100Z

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