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03/07/2023
Probing Graph Representations
Today we have a good theoretical understanding of the representational p...
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02/06/2023
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
In tasks like node classification, image segmentation, and named-entity ...
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01/31/2023
Are Defenses for Graph Neural Networks Robust?
A cursory reading of the literature suggests that we have made a lot of ...
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01/05/2023
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks
Randomized smoothing is one of the most promising frameworks for certify...
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12/09/2022
Adversarial Weight Perturbation Improves Generalization in Graph Neural Network
A lot of theoretical and empirical evidence shows that the flatter local...
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10/28/2022
Localized Randomized Smoothing for Collective Robustness Certification
Models for image segmentation, node classification and many other tasks ...
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10/15/2022
Unveiling the Sampling Density in Non-Uniform Geometric Graphs
A powerful framework for studying graphs is to consider them as geometri...
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10/26/2021
Robustness of Graph Neural Networks at Scale
Graph Neural Networks (GNNs) are increasingly important given their popu...
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10/21/2021
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness
End-to-end (geometric) deep learning has seen first successes in approxi...
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08/29/2020
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More
Existing techniques for certifying the robustness of models for discrete...
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07/03/2020
Scaling Graph Neural Networks with Approximate PageRank
Graph neural networks (GNNs) have emerged as a powerful approach for sol...
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10/31/2019
Certifiable Robustness to Graph Perturbations
Despite the exploding interest in graph neural networks there has been l...
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10/30/2019
Group Centrality Maximization for Large-scale Graphs
The study of vertex centrality measures is a key aspect of network analy...
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11/14/2018
Pitfalls of Graph Neural Network Evaluation
Semi-supervised node classification in graphs is a fundamental problem i...
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10/14/2018
Personalized Embedding Propagation: Combining Neural Networks on Graphs with Personalized PageRank
Neural message passing algorithms for semi-supervised classification on ...
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06/03/2018
Dual-Primal Graph Convolutional Networks
In recent years, there has been a surge of interest in developing deep l...
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03/02/2018
NetGAN: Generating Graphs via Random Walks
We propose NetGAN - the first implicit generative model for graphs able ...
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07/12/2017