Simon Geisler - RankMe

45 papers A* 15Misc 1Journal 28Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Adversarial Robustness of Graph Transformers. Trans. Mach. Learn. Res. Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann
2025	A*	`conf`	Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance. ICLR Dominik Fuchsgruber, Tim Postuvan, Stephan Günnemann, Simon Geisler
2025	J	`jnl`	LLM-Safety Evaluations Lack Robustness. CoRR Tim Beyer, Sophie Xhonneux, Simon Geisler, Gauthier Gidel, Leo Schwinn, Stephan Günnemann
2025	J	`jnl`	Long-Range Graph Wavelet Networks. CoRR Filippo Guerranti, Fabrizio Forte, Simon Geisler, Stephan Günnemann
2025	A*	`conf`	REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective. ICML Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Vincent Cohen-Addad, Johannes Gasteiger, Stephan Günnemann
2025	J	`jnl`	REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective. CoRR Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Vincent Cohen-Addad, Johannes Gasteiger, Stephan Günnemann
2025	J	`jnl`	SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation. CoRR Rafiq Kamel, Filippo Guerranti, Simon Geisler, Stephan Günnemann
2025	A*	`conf`	The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence. ICML Tom Wollschläger, Jannes Elstner, Simon Geisler, Vincent Cohen-Addad, Stephan Günnemann, Johannes Gasteiger
2025	J	`jnl`	The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence. CoRR Tom Wollschläger, Jannes Elstner, Simon Geisler, Vincent Cohen-Addad, Stephan Günnemann, Johannes Gasteiger
2024	J	`jnl`	Attacking Large Language Models with Projected Gradient Descent. CoRR Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Johannes Gasteiger, Stephan Günnemann
2024	J	`jnl`	Explainable Graph Neural Networks Under Fire. CoRR Zhong Li, Simon Geisler, Yuhang Wang, Stephan Günnemann, Matthijs van Leeuwen
2024	J	`jnl`	Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance. CoRR Dominik Fuchsgruber, Tim Postuvan, Stephan Günnemann, Simon Geisler
2024	J	`jnl`	Relaxing Graph Transformers for Adversarial Attacks. CoRR Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann
2024	J	`jnl`	Revisiting the Robust Alignment of Circuit Breakers. CoRR Leo Schwinn, Simon Geisler
2024	A*	`conf`	Spatio-Spectral Graph Neural Networks. NeurIPS Simon Geisler, Arthur Kosmala, Daniel Herbst, Stephan Günnemann
2024	J	`jnl`	Spatio-Spectral Graph Neural Networks. CoRR Simon Geisler, Arthur Kosmala, Daniel Herbst, 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`	Are Defenses for Graph Neural Networks Robust? CoRR Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski
2023	J	`jnl`	On the Adversarial Robustness of Graph Contrastive Learning Methods. CoRR Filippo Guerranti, Zinuo Yi, Anna Starovoit, Rafiq Kamel, Simon Geisler, Stephan Günnemann
2023	J	`jnl`	Poisoning × Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks. CoRR Ege Erdogan, Simon Geisler, Stephan Günnemann
2023	J	`jnl`	Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. CoRR Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann
2023	A*	`conf`	Revisiting Robustness in Graph Machine Learning. ICLR Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann
2023	J	`jnl`	Revisiting Robustness in Graph Machine Learning. CoRR Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann
2023	Misc	`conf`	Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. CoRL Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel
2023	J	`jnl`	Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. CoRR Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel
2023	A*	`conf`	Transformers Meet Directed Graphs. ICML Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru
2023	J	`jnl`	Transformers Meet Directed Graphs. CoRR Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru
2022	A*	`conf`	Are Defenses for Graph Neural Networks Robust? NeurIPS Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski
2022	J	`jnl`	Better, Faster Small Hazard Detection: Instance-Aware Techniques, Metrics and Benchmarking. IEEE Trans. Intell. Transp. Syst. Simon Geisler, Carlos Cunha, Ravi Kumar Satzoda
2022	A*	`conf`	Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. ICLR Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, 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`	Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. NeurIPS Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, 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`	Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. CoRR Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, 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	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	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	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
2018	—	`conf`	Time-Series Features for Predictive Policing. ISC2 Julio De Melo Borges, Daniel Ziehr, Michael Beigl, Nélio Cacho, Allan de M. Martins, Adelson Araujo, Leonardo C. T. Bezerra, Simon Geisler