Daniel Zügner

According to our database, Daniel Zügner authored at least 29 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

MatterGen: a generative model for inorganic materials design.

Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Sasha Shysheya, Jonathan Crabbé, Lixin Sun, Jake Smith, Ryota Tomioka, Tian Xie

CoRR, 2023

Adversarial Training for Graph Neural Networks.

Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

CoRR, 2023

Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics.

Marloes Arts, Victor Garcia Satorras, Chin-Wei Huang, Daniel Zügner, Marco Federici, Cecilia Clementi, Frank Noé, Robert Pinsler, Rianne van den Berg

CoRR, 2023

Training Differentially Private Graph Neural Networks with Random Walk Sampling.

Morgane Ayle, Jan Schuchardt, Lukas Gosch, Daniel Zügner, Stephan Günnemann

CoRR, 2023

Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions.

Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Adversarial Robustness of Graph Neural Networks.

Daniel Zügner

PhD thesis, 2022

On the Robustness and Anomaly Detection of Sparse Neural Networks.

Morgane Ayle, Bertrand Charpentier, John Rachwan, Daniel Zügner, Simon Geisler, Stephan Günnemann

CoRR, 2022

Winning the Lottery Ahead of Time: Efficient Early Network Pruning.

John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann

Proceedings of the International Conference on Machine Learning, 2022

End-to-End Learning of Probabilistic Hierarchies on Graphs.

Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann

Proceedings of the Tenth International Conference on Learning Representations, 2022

Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions.

Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Monte Carlo EM for Deep Time Series Anomaly Detection.

François-Xavier Aubet, Daniel Zügner, Jan Gasthaus

CoRR, 2021

A Study of Joint Graph Inference and Forecasting.

Daniel Zügner, François-Xavier Aubet, Victor Garcia Satorras, Tim Januschowski, Stephan Günnemann, Jan Gasthaus

CoRR, 2021

On Out-of-distribution Detection with Energy-based Models.

Sven Elflein, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

CoRR, 2021

Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification.

Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Robustness of Graph Neural Networks at Scale.

Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?

Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann

Proceedings of the 38th International Conference on Machine Learning, 2021

Language-Agnostic Representation Learning of Source Code from Structure and Context.

Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Adversarial Attacks on Graph Neural Networks: Perturbations and their Patterns.

Daniel Zügner, Oliver Borchert, Amir Akbarnejad, Stephan Günnemann

ACM Trans. Knowl. Discov. Data, 2020

Reliable Graph Neural Networks via Robust Aggregation.

Simon Geisler, Daniel Zügner, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts.

Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Certifiable Robustness of Graph Convolutional Networks under Structure Perturbations.

Daniel Zügner, Stephan Günnemann

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Group Centrality Maximization for Large-scale Graphs.

Eugenio Angriman, Alexander van der Grinten, Aleksandar Bojchevski, Daniel Zügner, Stephan Günnemann, Henning Meyerhenke

Proceedings of the Symposium on Algorithm Engineering and Experiments, 2020

2019

Oktoberfest Food Dataset.

Alexander Ziller, Julius Hansjakob, Vitalii Rusinov, Daniel Zügner, Peter Vogel, Stephan Günnemann

CoRR, 2019

Certifiable Robustness and Robust Training for Graph Convolutional Networks.

Daniel Zügner, Stephan Günnemann

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Adversarial Attacks on Graph Neural Networks via Meta Learning.

Daniel Zügner, Stephan Günnemann

Proceedings of the 7th International Conference on Learning Representations, 2019

Adversarial Attacks on Graph Neural Networks.

Daniel Zügner, Amir Akbarnejad, Stephan Günnemann

Proceedings of the 49. Jahrestagung der Gesellschaft für Informatik, 50 Jahre Gesellschaft für Informatik, 2019

2018

Adversarial Attacks on Neural Networks for Graph Data.

Daniel Zügner, Amir Akbarnejad, Stephan Günnemann

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

NetGAN: Generating Graphs via Random Walks.

Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann

Proceedings of the 35th International Conference on Machine Learning, 2018

2015

Pushing the limits of RFID: Empowering RFID-based Electronic Article Surveillance with Data Analytics Techniques.

Matthias Hauser, Daniel Zügner, Christoph Flath, Frédéric Thiesse

Proceedings of the International Conference on Information Systems, 2015