Daniel Zügner

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 41

Top Topics

Differentially Private

Diffusion Models

Top Venues

Publications

Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
Adversarial Training for Graph Neural Networks. CoRR (2023)
Morgane Ayle, Jan Schuchardt, Lukas Gosch, Daniel Zügner, Stephan Günnemann
Training Differentially Private Graph Neural Networks with Random Walk Sampling. CoRR (2023)
Marloes Arts, Victor Garcia Satorras, Chin-Wei Huang, Daniel Zügner, Marco Federici, Cecilia Clementi, Frank Noé, Robert Pinsler, Rianne van den Berg
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics. CoRR (2023)
Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Sasha Shysheya, Jonathan Crabbé, Lixin Sun, Jake Smith, Ryota Tomioka, Tian Xie
MatterGen: a generative model for inorganic materials design. CoRR (2023)
Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions. NeurIPS (2023)
Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann
End-to-End Learning of Probabilistic Hierarchies on Graphs. ICLR (2022)
John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann
Winning the Lottery Ahead of Time: Efficient Early Network Pruning. ICML (2022)
John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann
Winning the Lottery Ahead of Time: Efficient Early Network Pruning. CoRR (2022)
Morgane Ayle, Bertrand Charpentier, John Rachwan, Daniel Zügner, Simon Geisler, Stephan Günnemann
On the Robustness and Anomaly Detection of Sparse Neural Networks. CoRR (2022)
Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. ICLR (2022)
Sven Elflein, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
On Out-of-distribution Detection with Energy-based Models. CoRR (2021)
Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann
Language-Agnostic Representation Learning of Source Code from Structure and Context. ICLR (2021)
Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. CoRR (2021)
Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification. CoRR (2021)
Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann
Robustness of Graph Neural Networks at Scale. CoRR (2021)
Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification. NeurIPS (2021)
Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? ICML (2021)
Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann
Robustness of Graph Neural Networks at Scale. NeurIPS (2021)
Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann
Language-Agnostic Representation Learning of Source Code from Structure and Context. CoRR (2021)
François-Xavier Aubet, Daniel Zügner, Jan Gasthaus
Monte Carlo EM for Deep Time Series Anomaly Detection. CoRR (2021)
Daniel Zügner, François-Xavier Aubet, Victor Garcia Satorras, Tim Januschowski, Stephan Günnemann, Jan Gasthaus
A Study of Joint Graph Inference and Forecasting. CoRR (2021)
Daniel Zügner, Stephan Günnemann
Certifiable Robustness of Graph Convolutional Networks under Structure Perturbations. KDD (2020)
Daniel Zügner, Oliver Borchert, Amir Akbarnejad, Stephan Günnemann
Adversarial Attacks on Graph Neural Networks: Perturbations and their Patterns. ACM Trans. Knowl. Discov. Data 14 (5) (2020)
Simon Geisler, Daniel Zügner, Stephan Günnemann
Reliable Graph Neural Networks via Robust Aggregation. NeurIPS (2020)
Eugenio Angriman, Alexander van der Grinten, Aleksandar Bojchevski, Daniel Zügner, Stephan Günnemann, Henning Meyerhenke
Group Centrality Maximization for Large-scale Graphs. ALENEX (2020)
Simon Geisler, Daniel Zügner, Stephan Günnemann
Reliable Graph Neural Networks via Robust Aggregation. CoRR (2020)
Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts. NeurIPS (2020)
Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? CoRR (2020)
Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts. CoRR (2020)
Alexander Ziller, Julius Hansjakob, Vitalii Rusinov, Daniel Zügner, Peter Vogel, Stephan Günnemann
Oktoberfest Food Dataset. CoRR (2019)
Daniel Zügner, Amir Akbarnejad, Stephan Günnemann
Adversarial Attacks on Neural Networks for Graph Data. IJCAI (2019)
Daniel Zügner, Stephan Günnemann
Certifiable Robustness and Robust Training for Graph Convolutional Networks. CoRR (2019)
Eugenio Angriman, Alexander van der Grinten, Aleksandar Bojchevski, Daniel Zügner, Stephan Günnemann, Henning Meyerhenke
Group Centrality Maximization for Large-scale Graphs. CoRR (2019)
Daniel Zügner, Amir Akbarnejad, Stephan Günnemann
Adversarial Attacks on Graph Neural Networks. GI-Jahrestagung (2019)
Daniel Zügner, Stephan Günnemann
Adversarial Attacks on Graph Neural Networks via Meta Learning. ICLR (Poster) (2019)
Daniel Zügner, Stephan Günnemann
Certifiable Robustness and Robust Training for Graph Convolutional Networks. KDD (2019)
Daniel Zügner, Stephan Günnemann
Adversarial Attacks on Graph Neural Networks via Meta Learning. CoRR (2019)
Daniel Zügner, Amir Akbarnejad, Stephan Günnemann
Adversarial Attacks on Neural Networks for Graph Data. KDD (2018)
Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann
NetGAN: Generating Graphs via Random Walks. CoRR (2018)
Daniel Zügner, Amir Akbarnejad, Stephan Günnemann
Adversarial Attacks on Neural Networks for Graph Data. CoRR (2018)
Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann
NetGAN: Generating Graphs via Random Walks. ICML (2018)
Matthias Hauser, Daniel Zügner, Christoph Flath, Frédéric Thiesse
Pushing the limits of RFID: Empowering RFID-based Electronic Article Surveillance with Data Analytics Techniques. ICIS (2015)