Daniel Zügner
Title
Cited by
Cited by
Year
Adversarial attacks on neural networks for graph data
D Zügner, A Akbarnejad, S Günnemann
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
3502018
Netgan: Generating graphs via random walks
A Bojchevski, O Shchur, D Zügner, S Günnemann
International Conference on Machine Learning, 610-619, 2018
1932018
Adversarial attacks on graph neural networks via meta learning
D Zügner, S Günnemann
International Conference on Learning Representations, 2019
1552019
Certifiable robustness and robust training for graph convolutional networks
D Zügner, S Günnemann
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
752019
Pushing the limits of RFID: empowering RFID-based electronic article surveillance with data analytics techniques
M Hauser, D Zügner, C Flath, F Thiesse
192015
Certifiable robustness of graph convolutional networks under structure perturbations
D Zügner, S Günnemann
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
162020
Posterior network: Uncertainty estimation without ood samples via density-based pseudo-counts
B Charpentier, D Zügner, S Günnemann
arXiv preprint arXiv:2006.09239, 2020
92020
Adversarial attacks on graph neural networks: Perturbations and their patterns
D Zügner, O Borchert, A Akbarnejad, S Günnemann
ACM Transactions on Knowledge Discovery from Data (TKDD) 14 (5), 1-31, 2020
82020
Reliable graph neural networks via robust aggregation
S Geisler, D Zügner, S Günnemann
arXiv preprint arXiv:2010.15651, 2020
52020
Group Centrality Maximization for Large-scale Graphs
E Angriman, A van der Grinten, A Bojchevski, D Zügner, S Günnemann, ...
2020 Proceedings of the Twenty-Second Workshop on Algorithm Engineering and …, 2020
42020
Language-Agnostic Representation Learning of Source Code from Structure and Context
D Zügner, T Kirschstein, M Catasta, J Leskovec, S Günnemann
International Conference on Learning Representations, 2021
32021
Oktoberfest Food Dataset
A Ziller, J Hansjakob, V Rusinov, D Zügner, P Vogel, S Günnemann
arXiv preprint arXiv:1912.05007, 2019
22019
Attacking Graph Neural Networks at Scale
S Geisler, D Zügner, A Bojchevski, S Günnemann
Deep Learning for Graphs at AAAI Conference on Artificial Intelligence 2021 …, 2021
12021
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
AK Kopetzki, B Charpentier, D Zügner, S Giri, S Günnemann
International Conference on Machine Learning 2021, 2020
12020
On Out-of-distribution Detection with Energy-based Models
S Elflein, B Charpentier, D Zügner, S Günnemann
arXiv preprint arXiv:2107.08785, 2021
2021
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions
B Charpentier, O Borchert, D Zügner, S Geisler, S Günnemann
arXiv preprint arXiv:2105.04471, 2021
2021
Adversarial Attacks on Graph Neural Networks
D Zügner, A Akbarnejad, S Günnemann
INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik–Informatik für …, 2019
2019
Generative Adversarial Networks for Graphs
D Zügner
Universität Hamburg, 2017
2017
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Articles 1–18