Predict then Propagate: Graph Neural Networks meet Personalized PageRank J Klicpera, A Bojchevski, S Günnemann International Conference on Learning Representations (ICLR), 2019 | 1966* | 2019 |
Pitfalls of graph neural network evaluation O Shchur, M Mumme, A Bojchevski, S Günnemann Relational Representation Learning, NeurIPS 2018 Workshop, 2018 | 1418 | 2018 |
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking A Bojchevski, S Günnemann International Conference on Learning Representations (ICLR) 2018, 2018 | 781 | 2018 |
NetGAN: Generating Graphs via Random Walks A Bojchevski, O Shchur, D Zügner, S Günnemann International Conference on Machine Learning (ICML), 610-619, 2018 | 466 | 2018 |
Adversarial Attacks on Node Embeddings via Graph Poisoning A Bojchevski, S Günnemann International Conference on Machine Learning (ICML), 695-704, 2019 | 360 | 2019 |
Scaling graph neural networks with approximate pagerank A Bojchevski, J Gasteiger, B Perozzi, A Kapoor, M Blais, B Rózemberczki, ... Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 306 | 2020 |
Certifiable Robustness to Graph Perturbations A Bojchevski, S Günnemann Advances in Neural Information Processing Systems (NeurIPS), 8317-8328, 2019 | 145 | 2019 |
Combining neural networks with personalized pagerank for classification on graphs J Klicpera, A Bojchevski, S Günnemann International conference on learning representations, 2019 | 143 | 2019 |
Robustness of graph neural networks at scale S Geisler, T Schmidt, H Şirin, D Zügner, A Bojchevski, S Günnemann Advances in Neural Information Processing Systems 34, 7637-7649, 2021 | 130 | 2021 |
Efficient robustness certificates for discrete data: Sparsity-aware randomized smoothing for graphs, images and more A Bojchevski, J Gasteiger, S Günnemann International Conference on Machine Learning, 1003-1013, 2020 | 87 | 2020 |
Bayesian robust attributed graph clustering: Joint learning of partial anomalies and group structure A Bojchevski, S Günnemann AAAI Conference on Artificial Intelligence, 2018 | 81 | 2018 |
Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings A Bojchevski, Y Matkovic, S Günnemann International Conference on Knowledge Discovery and Data Mining (SIGKDD …, 2017 | 81 | 2017 |
Dual-primal graph convolutional networks F Monti, O Shchur, A Bojchevski, O Litany, S Günnemann, MM Bronstein Graph Embedding and Mining, ECML-PKDD 2019 Workshop, 2018 | 77 | 2018 |
Are defenses for graph neural networks robust? F Mujkanovic, S Geisler, S Günnemann, A Bojchevski Advances in Neural Information Processing Systems 35, 8954-8968, 2022 | 63 | 2022 |
Generalization of neural combinatorial solvers through the lens of adversarial robustness S Geisler, J Sommer, J Schuchardt, A Bojchevski, S Günnemann arXiv preprint arXiv:2110.10942, 2021 | 40 | 2021 |
LocText: relation extraction of protein localizations to assist database curation JM Cejuela, S Vinchurkar, T Goldberg, MS Prabhu Shankar, ... BMC bioinformatics 19, 1-11, 2018 | 35 | 2018 |
Adversarial weight perturbation improves generalization in graph neural networks Y Wu, A Bojchevski, H Huang Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 10417 …, 2023 | 28 | 2023 |
Is pagerank all you need for scalable graph neural networks A Bojchevski, J Klicpera, B Perozzi, M Blais, A Kapoor, M Lukasik, ... ACM KDD, MLG Workshop, 2019 | 28 | 2019 |
Conformal prediction sets for graph neural networks SH Zargarbashi, S Antonelli, A Bojchevski International Conference on Machine Learning, 12292-12318, 2023 | 27 | 2023 |
Or Litany, Stephan Günnemann, and Michael M Bronstein. Dual-primal graph convolutional networks F Monti, O Shchur, A Bojchevski arXiv preprint arXiv:1806.00770 3, 2018 | 24 | 2018 |