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Aleksandar Bojchevski
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Predict then Propagate: Graph Neural Networks meet Personalized PageRank
J Klicpera, A Bojchevski, S GŁnnemann
International Conference on Learning Representations (ICLR), 2019
1634*2019
Pitfalls of graph neural network evaluation
O Shchur, M Mumme, A Bojchevski, S GŁnnemann
Relational Representation Learning, NeurIPS 2018 Workshop, 2018
11562018
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
A Bojchevski, S GŁnnemann
International Conference on Learning Representations (ICLR) 2018, 2018
6782018
NetGAN: Generating Graphs via Random Walks
A Bojchevski, O Shchur, D ZŁgner, S GŁnnemann
International Conference on Machine Learning (ICML), 610-619, 2018
4152018
Adversarial Attacks on Node Embeddings via Graph Poisoning
A Bojchevski, S GŁnnemann
International Conference on Machine Learning (ICML), 695-704, 2019
3272019
Scaling graph neural networks with approximate pagerank
A Bojchevski, J Gasteiger, B Perozzi, A Kapoor, M Blais, B Růzemberczki, ...
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge†…, 2020
2612020
Certifiable Robustness to Graph Perturbations
A Bojchevski, S GŁnnemann
Advances in Neural Information Processing Systems (NeurIPS), 8317-8328, 2019
1252019
Combining neural networks with personalized pagerank for classification on graphs
J Klicpera, A Bojchevski, S GŁnnemann
International conference on learning representations, 2019
1162019
Robustness of graph neural networks at scale
S Geisler, T Schmidt, H Şirin, D ZŁgner, A Bojchevski, S GŁnnemann
Advances in Neural Information Processing Systems 34, 7637-7649, 2021
952021
Bayesian robust attributed graph clustering: Joint learning of partial anomalies and group structure
A Bojchevski, S GŁnnemann
AAAI Conference on Artificial Intelligence, 2018
802018
Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings
A Bojchevski, Y Matkovic, S GŁnnemann
International Conference on Knowledge Discovery and Data Mining (SIGKDD†…, 2017
732017
Efficient robustness certificates for discrete data: Sparsity-aware randomized smoothing for graphs, images and more
A Bojchevski, J Gasteiger, S GŁnnemann
International Conference on Machine Learning, 1003-1013, 2020
722020
Dual-primal graph convolutional networks
F Monti, O Shchur, A Bojchevski, O Litany, S GŁnnemann, MM Bronstein
Graph Embedding and Mining, ECML-PKDD 2019 Workshop, 2018
692018
Are defenses for graph neural networks robust?
F Mujkanovic, S Geisler, S GŁnnemann, A Bojchevski
Advances in Neural Information Processing Systems 35, 8954-8968, 2022
442022
Generalization of neural combinatorial solvers through the lens of adversarial robustness
S Geisler, J Sommer, J Schuchardt, A Bojchevski, S GŁnnemann
arXiv preprint arXiv:2110.10942, 2021
332021
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
302018
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
252019
Or Litany, Stephan GŁnnemann, and Michael M Bronstein. Dual-primal graph convolutional networks
F Monti, O Shchur, A Bojchevski
arXiv preprint arXiv:1806.00770 3, 2018
232018
Group centrality maximization for large-scale graphs
E Angriman, A van der Grinten, A Bojchevski, D ZŁgner, S GŁnnemann, ...
2020 Proceedings of the twenty-second workshop on Algorithm Engineering and†…, 2020
192020
Completing the picture: Randomized smoothing suffers from the curse of dimensionality for a large family of distributions
Y Wu, A Bojchevski, A Kuvshinov, S GŁnnemann
International Conference on Artificial Intelligence and Statistics, 3763-3771, 2021
172021
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