Daniel Zügner

45 papers A* 16A 1C 1Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A generative model for inorganic materials design. Nat. Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Zilong Wang, Aliaksandra Shysheya, Jonathan Crabbé, Shoko Ueda, Roberto Sordillo, Lixin Sun, Jake Smith, Bichlien Nguyen, Hannes Schulz, Sarah Lewis, Chin-Wei Huang, Ziheng Lu, Yichi Zhou, Han Yang, Hongxia Hao, Jielan Li, Chunlei Yang, Wenjie Li, Ryota Tomioka, Tian Xie
2024	A*	`conf`	Expected Probabilistic Hierarchies. NeurIPS Marcel Kollovieh, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
2023	J	`jnl`	Adversarial Training for Graph Neural Networks. CoRR Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
2023	A*	`conf`	Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions. NeurIPS Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
2023	J	`jnl`	MatterGen: a generative model for inorganic materials design. CoRR Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Sasha Shysheya, Jonathan Crabbé, Lixin Sun, Jake Smith, Ryota Tomioka, Tian Xie
2023	J	`jnl`	Training Differentially Private Graph Neural Networks with Random Walk Sampling. CoRR Morgane Ayle, Jan Schuchardt, Lukas Gosch, Daniel Zügner, Stephan Günnemann
2023	J	`jnl`	Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics. CoRR Marloes Arts, Victor Garcia Satorras, Chin-Wei Huang, Daniel Zügner, Marco Federici, Cecilia Clementi, Frank Noé, Robert Pinsler, Rianne van den Berg
2022	—	`—`	Adversarial Robustness of Graph Neural Networks. Daniel Zügner
2022	A*	`conf`	End-to-End Learning of Probabilistic Hierarchies on Graphs. ICLR Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann
2022	A*	`conf`	Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. ICLR Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann
2022	J	`jnl`	On the Robustness and Anomaly Detection of Sparse Neural Networks. CoRR Morgane Ayle, Bertrand Charpentier, John Rachwan, Daniel Zügner, Simon Geisler, Stephan Günnemann
2022	A*	`conf`	Winning the Lottery Ahead of Time: Efficient Early Network Pruning. ICML John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann
2022	J	`jnl`	Winning the Lottery Ahead of Time: Efficient Early Network Pruning. CoRR John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann
2021	J	`jnl`	A Study of Joint Graph Inference and Forecasting. CoRR Daniel Zügner, François-Xavier Aubet, Victor Garcia Satorras, Tim Januschowski, Stephan Günnemann, Jan Gasthaus
2021	A*	`conf`	Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? ICML Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann
2021	A*	`conf`	Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification. NeurIPS Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann
2021	J	`jnl`	Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification. CoRR Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann
2021	A*	`conf`	Language-Agnostic Representation Learning of Source Code from Structure and Context. ICLR Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann
2021	J	`jnl`	Language-Agnostic Representation Learning of Source Code from Structure and Context. CoRR Daniel Zügner, Tobias Kirschstein, Michele Catasta, Jure Leskovec, Stephan Günnemann
2021	J	`jnl`	Monte Carlo EM for Deep Time Series Anomaly Detection. CoRR François-Xavier Aubet, Daniel Zügner, Jan Gasthaus
2021	J	`jnl`	Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. CoRR Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann
2021	J	`jnl`	On Out-of-distribution Detection with Energy-based Models. CoRR Sven Elflein, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
2021	A*	`conf`	Robustness of Graph Neural Networks at Scale. NeurIPS Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann
2021	J	`jnl`	Robustness of Graph Neural Networks at Scale. CoRR Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann
2020	J	`jnl`	Adversarial Attacks on Graph Neural Networks: Perturbations and their Patterns. ACM Trans. Knowl. Discov. Data Daniel Zügner, Oliver Borchert, Amir Akbarnejad, Stephan Günnemann
2020	A*	`conf`	Certifiable Robustness of Graph Convolutional Networks under Structure Perturbations. KDD Daniel Zügner, Stephan Günnemann
2020	J	`jnl`	Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? CoRR Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann
2020	A	`conf`	Group Centrality Maximization for Large-scale Graphs. ALENEX Eugenio Angriman, Alexander van der Grinten, Aleksandar Bojchevski, Daniel Zügner, Stephan Günnemann, Henning Meyerhenke
2020	A*	`conf`	Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts. NeurIPS Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
2020	J	`jnl`	Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts. CoRR Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
2020	A*	`conf`	Reliable Graph Neural Networks via Robust Aggregation. NeurIPS Simon Geisler, Daniel Zügner, Stephan Günnemann
2020	J	`jnl`	Reliable Graph Neural Networks via Robust Aggregation. CoRR Simon Geisler, Daniel Zügner, Stephan Günnemann
2019	—	`conf`	Adversarial Attacks on Graph Neural Networks via Meta Learning. ICLR (Poster) Daniel Zügner, Stephan Günnemann
2019	J	`jnl`	Adversarial Attacks on Graph Neural Networks via Meta Learning. CoRR Daniel Zügner, Stephan Günnemann
2019	—	`conf`	Adversarial Attacks on Graph Neural Networks. GI-Jahrestagung Daniel Zügner, Amir Akbarnejad, Stephan Günnemann
2019	A*	`conf`	Adversarial Attacks on Neural Networks for Graph Data. IJCAI Daniel Zügner, Amir Akbarnejad, Stephan Günnemann
2019	A*	`conf`	Certifiable Robustness and Robust Training for Graph Convolutional Networks. KDD Daniel Zügner, Stephan Günnemann
2019	J	`jnl`	Certifiable Robustness and Robust Training for Graph Convolutional Networks. CoRR Daniel Zügner, Stephan Günnemann
2019	J	`jnl`	Group Centrality Maximization for Large-scale Graphs. CoRR Eugenio Angriman, Alexander van der Grinten, Aleksandar Bojchevski, Daniel Zügner, Stephan Günnemann, Henning Meyerhenke
2019	J	`jnl`	Oktoberfest Food Dataset. CoRR Alexander Ziller, Julius Hansjakob, Vitalii Rusinov, Daniel Zügner, Peter Vogel, Stephan Günnemann
2018	A*	`conf`	Adversarial Attacks on Neural Networks for Graph Data. KDD Daniel Zügner, Amir Akbarnejad, Stephan Günnemann
2018	J	`jnl`	Adversarial Attacks on Neural Networks for Graph Data. CoRR Daniel Zügner, Amir Akbarnejad, Stephan Günnemann
2018	A*	`conf`	NetGAN: Generating Graphs via Random Walks. ICML Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann
2018	J	`jnl`	NetGAN: Generating Graphs via Random Walks. CoRR Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann
2015	C	`conf`	Pushing the limits of RFID: Empowering RFID-based Electronic Article Surveillance with Data Analytics Techniques. ICIS Matthias Hauser, Daniel Zügner, Christoph Flath, Frédéric Thiesse