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Aleksandar Bojchevski
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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
14182018
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
A Bojchevski, S Günnemann
International Conference on Learning Representations (ICLR) 2018, 2018
7812018
NetGAN: Generating Graphs via Random Walks
A Bojchevski, O Shchur, D Zügner, S Günnemann
International Conference on Machine Learning (ICML), 610-619, 2018
4662018
Adversarial Attacks on Node Embeddings via Graph Poisoning
A Bojchevski, S Günnemann
International Conference on Machine Learning (ICML), 695-704, 2019
3602019
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
3062020
Certifiable Robustness to Graph Perturbations
A Bojchevski, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 8317-8328, 2019
1452019
Combining neural networks with personalized pagerank for classification on graphs
J Klicpera, A Bojchevski, S Günnemann
International conference on learning representations, 2019
1432019
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
1302021
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
872020
Bayesian robust attributed graph clustering: Joint learning of partial anomalies and group structure
A Bojchevski, S Günnemann
AAAI Conference on Artificial Intelligence, 2018
812018
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
812017
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
772018
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
632022
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
402021
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
352018
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
282023
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
282019
Conformal prediction sets for graph neural networks
SH Zargarbashi, S Antonelli, A Bojchevski
International Conference on Machine Learning, 12292-12318, 2023
272023
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
242018
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