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ORCIDAleksandar Bojchevski
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2020 – today
- 2024
[c27]Vijay Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski:
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks. ICLR 2024- [c26]Soroush H. Zargarbashi, Aleksandar Bojchevski:
Conformal Inductive Graph Neural Networks. ICLR 2024 - [c25]Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski:
Robust Yet Efficient Conformal Prediction Sets. ICML 2024 - [i25]Vijay Lingam, Atula Tejaswi, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi:
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors. CoRR abs/2405.19597 (2024) - [i24]Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski:
Robust Yet Efficient Conformal Prediction Sets. CoRR abs/2407.09165 (2024) - [i23]Soroush H. Zargarbashi, Aleksandar Bojchevski:
Conformal Inductive Graph Neural Networks. CoRR abs/2407.09173 (2024) - [i22]Salah Ghamizi, Aleksandar Bojchevski, Aoxiang Ma, Jun Cao:
SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power Grids. CoRR abs/2407.12421 (2024) - 2023
- [c24]Yihan Wu, Aleksandar Bojchevski, Heng Huang:
Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks. AAAI 2023: 10417-10425 - [c23]Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski:
Probing Graph Representations. AISTATS 2023: 11630-11649 - [c22]Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie:
Unveiling the sampling density in non-uniform geometric graphs. ICLR 2023 - [c21]Jan Schuchardt, Tom Wollschläger, Aleksandar Bojchevski, Stephan Günnemann:
Localized Randomized Smoothing for Collective Robustness Certification. ICLR 2023 - [c20]Soroush H. Zargarbashi, Simone Antonelli, Aleksandar Bojchevski:
Conformal Prediction Sets for Graph Neural Networks. ICML 2023: 12292-12318 - [c19]Nimrah Mustafa, Aleksandar Bojchevski, Rebekka Burkholz:
Are GATs Out of Balance? NeurIPS 2023 - [c18]Yan Scholten, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann:
Hierarchical Randomized Smoothing. NeurIPS 2023 - [i21]Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann:
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. CoRR abs/2301.02039 (2023) - [i20]Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski:
Are Defenses for Graph Neural Networks Robust? CoRR abs/2301.13694 (2023) - [i19]Jan Schuchardt, Aleksandar Bojchevski, Johannes Gasteiger, Stephan Günnemann:
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks. CoRR abs/2302.02829 (2023) - [i18]Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski:
Probing Graph Representations. CoRR abs/2303.03951 (2023) - [i17]Nimrah Mustafa, Aleksandar Bojchevski, Rebekka Burkholz:
Are GATs Out of Balance? CoRR abs/2310.07235 (2023) - [i16]Yan Scholten, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann:
Hierarchical Randomized Smoothing. CoRR abs/2310.16221 (2023) - 2022
- [c17]Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann:
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. ICLR 2022 - [c16]Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski:
Are Defenses for Graph Neural Networks Robust? NeurIPS 2022 - [c15]Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann:
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. NeurIPS 2022 - [i15]Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok
, Ron Levie:
Unveiling the Sampling Density in Non-Uniform Geometric Graphs. CoRR abs/2210.08219 (2022) - [i14]Jan Schuchardt, Tom Wollschläger, Aleksandar Bojchevski, Stephan Günnemann:
Localized Randomized Smoothing for Collective Robustness Certification. CoRR abs/2210.16140 (2022) - [i13]Yihan Wu, Aleksandar Bojchevski, Heng Huang:
Adversarial Weight Perturbation Improves Generalization in Graph Neural Network. CoRR abs/2212.04983 (2022) - 2021
- [c14]Yihan Wu, Aleksandar Bojchevski, Aleksei Kuvshinov, Stephan Günnemann:
Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions. AISTATS 2021: 3763-3771 - [c13]Jan Schuchardt, Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann:
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks. ICLR 2021 - [c12]Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann:
Robustness of Graph Neural Networks at Scale. NeurIPS 2021: 7637-7649 - [i12]Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann:
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. CoRR abs/2110.10942 (2021) - [i11]Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann:
Robustness of Graph Neural Networks at Scale. CoRR abs/2110.14038 (2021) - 2020
- [b1]Aleksandar Bojchevski:
Machine Learning on Graphs in the Presence of Noise and Adversaries. Technical University of Munich, Germany, 2020 - [c11]Eugenio Angriman, Alexander van der Grinten, Aleksandar Bojchevski, Daniel Zügner, Stephan Günnemann, Henning Meyerhenke:
Group Centrality Maximization for Large-scale Graphs. ALENEX 2020: 56-69 - [c10]Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann:
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More. ICML 2020: 1003-1013 - [c9]Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. KDD 2020: 2464-2473 - [i10]Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. CoRR abs/2007.01570 (2020) - [i9]Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann:
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More. CoRR abs/2008.12952 (2020)
2010 – 2019
- 2019
- [c8]Johannes Klicpera, Aleksandar Bojchevski, Stephan Günnemann:
Predict then Propagate: Graph Neural Networks meet Personalized PageRank. ICLR (Poster) 2019 - [c7]Aleksandar Bojchevski, Stephan Günnemann:
Adversarial Attacks on Node Embeddings via Graph Poisoning. ICML 2019: 695-704 - [c6]Aleksandar Bojchevski, Stephan Günnemann:
Certifiable Robustness to Graph Perturbations. NeurIPS 2019: 8317-8328 - [i8]Eugenio Angriman, Alexander van der Grinten, Aleksandar Bojchevski, Daniel Zügner, Stephan Günnemann, Henning Meyerhenke:
Group Centrality Maximization for Large-scale Graphs. CoRR abs/1910.13874 (2019) - [i7]Aleksandar Bojchevski, Stephan Günnemann:
Certifiable Robustness to Graph Perturbations. CoRR abs/1910.14356 (2019) - 2018
- [j2]Juan Miguel Cejuela, Shrikant Vinchurkar, Tatyana Goldberg, Madhukar Sollepura Prabhu Shankar, Ashish Baghudana, Aleksandar Bojchevski, Carsten Uhlig, André Ofner, Pandu Raharja-Liu, Lars Juhl Jensen, Burkhard Rost:
LocText: relation extraction of protein localizations to assist database curation. BMC Bioinform. 19(1): 15:1-15:11 (2018) - [c5]Aleksandar Bojchevski, Stephan Günnemann:
Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure. AAAI 2018: 2738-2745 - [c4]Oleksandr Shchur, Aleksandar Bojchevski, Mohamed Farghal, Stephan Günnemann, Yusuf Saber:
Anomaly Detection in Car-Booking Graphs. ICDM Workshops 2018: 604-607 - [c3]Aleksandar Bojchevski, Stephan Günnemann:
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking. ICLR (Poster) 2018 - [c2]Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann:
NetGAN: Generating Graphs via Random Walks. ICML 2018: 609-618 - [i6]Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann:
NetGAN: Generating Graphs via Random Walks. CoRR abs/1803.00816 (2018) - [i5]Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, Michael M. Bronstein:
Dual-Primal Graph Convolutional Networks. CoRR abs/1806.00770 (2018) - [i4]Aleksandar Bojchevski, Stephan Günnemann:
Adversarial Attacks on Node Embeddings. CoRR abs/1809.01093 (2018) - [i3]Johannes Klicpera, Aleksandar Bojchevski, Stephan Günnemann:
Personalized Embedding Propagation: Combining Neural Networks on Graphs with Personalized PageRank. CoRR abs/1810.05997 (2018) - [i2]Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski, Stephan Günnemann:
Pitfalls of Graph Neural Network Evaluation. CoRR abs/1811.05868 (2018) - 2017
- [j1]Juan Miguel Cejuela, Aleksandar Bojchevski, Carsten Uhlig, Rustem Bekmukhametov, Sanjeev Kumar Karn, Shpend Mahmuti, Ashish Baghudana, Ankit Dubey, Venkata P. Satagopam, Burkhard Rost:
nala: text mining natural language mutation mentions. Bioinform. 33(12): 1852-1858 (2017) - [c1]Aleksandar Bojchevski, Yves Matkovic, Stephan Günnemann:
Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings. KDD 2017: 737-746 - [i1]Aleksandar Bojchevski, Stephan Günnemann:
Deep Gaussian Embedding of Attributed Graphs: Unsupervised Inductive Learning via Ranking. CoRR abs/1707.03815 (2017)
Coauthor Index
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last updated on 2024-09-04 01:23 CEST by the dblp team
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