Publications
2024
| Soroush H. Zargarbashi, and Aleksandar Bojchevski, Conformal Inductive Graph Neural Networks, in International Conference on Learning Representations, ICLR 2024 |
| Vijay Lingam, Sadegh Mohammad Akhondzadeh, and Aleksandar Bojchevski, Rethinking Label Poisoning for GNNs: Pitfalls and Attacks, in International Conference on Learning Representations, ICLR 2024 |
2023
| Jan Scholten, Jan Schuchardt, Aleksandar Bojchevski, and Stephan Gunnemann, Hierarchical Randomized Smoothing, in Neural Information Processing Systems, NeurIPS 2023 [arXiv] |
| Nimrah Mustafa, Aleksandar Bojchevski, and Rebekka Burkholz, Are GATs Out of Balance?, in Neural Information Processing Systems, NeurIPS 2023 [arXiv] |
| Soroush H. Zargarbashi, Simone Antonelli, and Aleksandar Bojchevski, Conformal Prediction Sets for Graph Neural Networks, in International Conference on Machine Learning, ICML 2023 |
| Sadegh Mohammad Akhondzadeh, Vijay Lingam, and Aleksandar Bojchevski, Probing Graph Representations, in International Conference on Artificial Intelligence and Statistics, AISTATS 2023 |
| Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, and Ron Levie, Unveiling the Sampling Density in Non-uniform Geometric Graphs in International Conference on Learning Representation, ICLR 2023 [arXiv] |
| Jan Schuchardt, Tom Wollschläger, Aleksandar Bojchevski, and Stephan Günnemann, Localized Randomized Smoothing for Collective Robustness Certification, in International Conference on Learning Representation, ICLR 2023 [arXiv] |
| Yihan Wu, Aleksandar Bojchevski, and Heng Huang, Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks, in Conference on Artificial Intelligence, AAAI 2023 |
2022
| Felix Mujkanovic, Simon Geisler, Stephan Günnemann, and Aleksandar Bojchevski, Are Defenses for Graph Neural Networks Robust?, in In Neural Information Processing Systems, NeurIPS 2022 |
| Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, and Stephan Günnemann, Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks, in Neural Information Processing Systems, NeurIPS 2022 |
| Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, and Stephan Günnemann, Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness, in International Conference on Learning Representation, ICLR 2022 |
2021
| Simon Geisler, Thomas Schmidt, Hakan Şirin, Daniel Zügner, Aleksandar Bojchevski, and Stephan Günnemann, Robustness of Graph Neural Networks at Scale, in Neural Information Processing Systems, NeurIPS 2021 |
| Jan Schuchardt, Aleksandar Bojchevski, Johannes Gasteiger, and Stephan Günnemann, Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks, in International Conference on Learning Representations, ICLR 2021 |
| Yihan Wu, Aleksandar Bojchevski, Aleksei Kuvshinov, and Stephan Günnemann, Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions, in International Conference on Artificial Intelligence and Statistics, AISTATS 2021 |
2020
| Aleksandar Bojchevski, Johannes Gasteiger, and Stephan Günnemann, Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More, in International Conference on Machine Learning, ICML 2020 |
| Aleksandar Bojchevski*, Johannes Gasteiger*, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, and Stephan Günnemann, Scaling Graph Neural Networks with Approximate PageRank, in International Conference on Knowledge Discovery and Data Mining, KDD 2020 |
| Eugenio Angriman, Alexander Grinten, Aleksandar Bojchevski, Daniel Zügner, Stephan Günnemann, and Henning Meyerhenke, Group Centrality Maximization for Large-scale Graphs, in Symposium on Algorithm Engineering and Experiments, ALENEX 2020 |
2019
| Aleksandar Bojchevski, and Stephan Günnemann, Certifiable Robustness to Graph Perturbations, in Neural Information Processing Systems, NeurIPS 2019 |
| Aleksandar Bojchevski, and Stephan Günnemann, Adversarial Attacks on Node Embeddings via Graph Poisoning, in International Conference on Machine Learning, ICML 2019 |
| Johannes Gasteiger, Aleksandar Bojchevski, and Stephan Günnemann, Predict then Propagate: Graph Neural Networks meet Personalized PageRank, in International Conference on Learning Representations, ICLR 2019 |
2018
| Aleksandar Bojchevski*, Oleksandr Shchur*, Daniel Zügner*, and Stephan Günnemann, NetGAN: Generating Graphs via Random Walks, in International Conference on Machine Learning, ICML 2018 |
| Aleksandar Bojchevski, and Stephan Günnemann, Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking, in International Conference on Learning Representations, ICLR 2018 |
| Aleksandar Bojchevski, and Stephan Günnemann, Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure, in Conference on Artificial Intelligence, AAAI 2018 |
| Juan Miguel Cejuela, Shrikant Vinchurkar, Tatyana Goldberg, Madhukar S. Prabhu Shankar, Ashish Baghudana, Aleksandar Bojchevski, Carsten Uhlig, André Ofner, Pandu Raharja-Liu, Lars Juhl Jensen, and others, LocText: Relation Extraction of Protein Localizations to Assist Database Curation, BMC Bioinformatics 2018 |
2017
| Aleksandar Bojchevski, Yves Matkovic, and Stephan Günnemann, Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings, in International Conference on Knowledge Discovery and Data Mining, KDD 2017 |
| Juan Miguel Cejuela, Aleksandar Bojchevski, Carsten Uhlig, Rustem Bekmukhametov, Sanjeev Kumar Karn, Shpend Mahmuti, Ashish Baghudana, Ankit Dubey, Venkata P Satagopam, and Burkhard Rost, nala: Text Mining Natural Language Mutation Mentions, Bioinformatics 2017 |