Time-Series Features for Predictive Policing. - Julio De Melo Borges; Daniel Ziehr; Michael Beigl; Nélio Cacho; Allan de M. Martins; Adelson Araujo; Leonardo C. T. Bezerra; Simon Geisler (ISC2, 2018)

Reliable Graph Neural Networks via Robust Aggregation. - Simon Geisler; Daniel Zügner; Stephan Günnemann (NeurIPS, 2020)

Robustness of Graph Neural Networks at Scale. - Simon Geisler; Tobias Schmidt; Hakan Sirin; Daniel Zügner; Aleksandar Bojchevski; Stephan Günnemann (NeurIPS, 2021)

Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification. - Maximilian Stadler; Bertrand Charpentier; Simon Geisler; Daniel Zügner; Stephan Günnemann (NeurIPS, 2021)

Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. - Bertrand Charpentier; Oliver Borchert; Daniel Zügner; Simon Geisler; Stephan Günnemann (ICLR, 2022)

Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. - Simon Geisler; Johanna Sommer; Jan Schuchardt; Aleksandar Bojchevski; Stephan Günnemann (ICLR, 2022)

Winning the Lottery Ahead of Time: Efficient Early Network Pruning. - John Rachwan; Daniel Zügner; Bertrand Charpentier; Simon Geisler; Morgane Ayle; Stephan Günnemann (ICML, 2022)

Are Defenses for Graph Neural Networks Robust? - Felix Mujkanovic; Simon Geisler; Stephan Günnemann; Aleksandar Bojchevski (NeurIPS, 2022)

Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. - Yan Scholten; Jan Schuchardt; Simon Geisler; Aleksandar Bojchevski; Stephan Günnemann (NeurIPS, 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)

Better, Faster Small Hazard Detection: Instance-Aware Techniques, Metrics and Benchmarking. - Simon Geisler; Carlos Cunha; Ravi Kumar Satzoda (IEEE Trans. Intell. Transp. Syst., 2022)

Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. - Jianxiang Feng; Jongseok Lee; Simon Geisler; Stephan Günnemann; Rudolph Triebel (CoRL, 2023)

Revisiting Robustness in Graph Machine Learning. - Lukas Gosch; Daniel Sturm 002; Simon Geisler; Stephan Günnemann (ICLR, 2023)

Transformers Meet Directed Graphs. - Simon Geisler; Yujia Li 001; Daniel J. Mankowitz; Ali Taylan Cemgil; Stephan Günnemann; Cosmin Paduraru (ICML, 2023)

Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions. - Lukas Gosch; Simon Geisler; Daniel Sturm 002; Bertrand Charpentier; Daniel Zügner; Stephan Günnemann (NeurIPS, 2023)

Adversarial Training for Graph Neural Networks. - Lukas Gosch; Simon Geisler; Daniel Sturm 002; Bertrand Charpentier; Daniel Zügner; Stephan Günnemann (CoRR, 2023)

On the Adversarial Robustness of Graph Contrastive Learning Methods. - Filippo Guerranti; Zinuo Yi; Anna Starovoit; Rafiq Kamel; Simon Geisler; Stephan Günnemann (CoRR, 2023)

Poisoning × Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks. - Ege Erdogan; Simon Geisler; Stephan Günnemann (CoRR, 2023)

Spatio-Spectral Graph Neural Networks. - Simon Geisler; Arthur Kosmala; Daniel Herbst; Stephan Günnemann (NeurIPS, 2024)

Attacking Large Language Models with Projected Gradient Descent. - Simon Geisler; Tom Wollschläger; M. H. I. Abdalla; Johannes Gasteiger; Stephan Günnemann (CoRR, 2024)

Explainable Graph Neural Networks Under Fire. - Zhong Li 002; Simon Geisler; Yuhang Wang; Stephan Günnemann; Matthijs van Leeuwen (CoRR, 2024)

Relaxing Graph Transformers for Adversarial Attacks. - Philipp Foth; Lukas Gosch; Simon Geisler; Leo Schwinn; Stephan Günnemann (CoRR, 2024)

Revisiting the Robust Alignment of Circuit Breakers. - Leo Schwinn; Simon Geisler (CoRR, 2024)

Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance. - Dominik Fuchsgruber; Tim Postuvan; Stephan Günnemann; Simon Geisler (ICLR, 2025)

REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective. - Simon Geisler; Tom Wollschläger; M. H. I. Abdalla; Vincent Cohen-Addad; Johannes Gasteiger; Stephan Günnemann (CoRR, 2025)

The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence. - Tom Wollschläger; Jannes Elstner; Simon Geisler; Vincent Cohen-Addad; Stephan Günnemann; Johannes Gasteiger (CoRR, 2025)

LLM-Safety Evaluations Lack Robustness. - Tim Beyer; Sophie Xhonneux; Simon Geisler; Gauthier Gidel; Leo Schwinn; Stephan Günnemann (CoRR, 2025)

SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation. - Rafiq Kamel; Filippo Guerranti; Simon Geisler; Stephan Günnemann (CoRR, 2025)