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Simon Geisler
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2020 – today
- 2024
- [i21]Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Johannes Gasteiger, Stephan Günnemann:
Attacking Large Language Models with Projected Gradient Descent. CoRR abs/2402.09154 (2024) - [i20]Simon Geisler, Arthur Kosmala, Daniel Herbst, Stephan Günnemann:
Spatio-Spectral Graph Neural Networks. CoRR abs/2405.19121 (2024) - [i19]Zhong Li, Simon Geisler, Yuhang Wang, Stephan Günnemann, Matthijs van Leeuwen:
Explainable Graph Neural Networks Under Fire. CoRR abs/2406.06417 (2024) - [i18]Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann:
Relaxing Graph Transformers for Adversarial Attacks. CoRR abs/2407.11764 (2024) - [i17]Leo Schwinn, Simon Geisler:
Revisiting the Robust Alignment of Circuit Breakers. CoRR abs/2407.15902 (2024) - [i16]Dominik Fuchsgruber, Tim Postuvan, Stephan Günnemann, Simon Geisler:
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance. CoRR abs/2410.16935 (2024) - 2023
- [c13]Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel:
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. CoRL 2023: 3214-3241 - [c12]Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann:
Revisiting Robustness in Graph Machine Learning. ICLR 2023 - [c11]Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru:
Transformers Meet Directed Graphs. ICML 2023: 11144-11172 - [c10]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 - [i15]Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann:
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. CoRR abs/2301.02039 (2023) - [i14]Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski:
Are Defenses for Graph Neural Networks Robust? CoRR abs/2301.13694 (2023) - [i13]Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru:
Transformers Meet Directed Graphs. CoRR abs/2302.00049 (2023) - [i12]Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann:
Revisiting Robustness in Graph Machine Learning. CoRR abs/2305.00851 (2023) - [i11]Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann:
Adversarial Training for Graph Neural Networks. CoRR abs/2306.15427 (2023) - [i10]Jianxiang Feng, Jongseok Lee, Simon Geisler, Stephan Günnemann, Rudolph Triebel:
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning. CoRR abs/2311.06481 (2023) - [i9]Filippo Guerranti, Zinuo Yi, Anna Starovoit, Rafiq Kamel, Simon Geisler, Stephan Günnemann:
On the Adversarial Robustness of Graph Contrastive Learning Methods. CoRR abs/2311.17853 (2023) - [i8]Ege Erdogan, Simon Geisler, Stephan Günnemann:
Poisoning × Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks. CoRR abs/2312.05502 (2023) - 2022
- [j1]Simon Geisler
, Carlos Cunha
Better, Faster Small Hazard Detection: Instance-Aware Techniques, Metrics and Benchmarking. IEEE Trans. Intell. Transp. Syst. 23(7): 9062-9077 (2022) - [c9]Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann:
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. ICLR 2022 - [c8]Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann:
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. ICLR 2022 - [c7]John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann:
Winning the Lottery Ahead of Time: Efficient Early Network Pruning. ICML 2022: 18293-18309 - [c6]Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski:
Are Defenses for Graph Neural Networks Robust? NeurIPS 2022 - [c5]Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann:
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. NeurIPS 2022 - [i7]John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann:
Winning the Lottery Ahead of Time: Efficient Early Network Pruning. CoRR abs/2206.10451 (2022) - [i6]Morgane Ayle, Bertrand Charpentier, John Rachwan, Daniel Zügner, Simon Geisler, Stephan Günnemann:
On the Robustness and Anomaly Detection of Sparse Neural Networks. CoRR abs/2207.04227 (2022) - 2021
- [c4]Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann:
Robustness of Graph Neural Networks at Scale. NeurIPS 2021: 7637-7649 - [c3]Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann:
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification. NeurIPS 2021: 18033-18048 - [i5]Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann:
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. CoRR abs/2105.04471 (2021) - [i4]Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann:
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. CoRR abs/2110.10942 (2021) - [i3]Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann:
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification. CoRR abs/2110.14012 (2021) - [i2]Simon Geisler, Tobias Schmidt, Hakan Sirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann:
Robustness of Graph Neural Networks at Scale. CoRR abs/2110.14038 (2021) - 2020
- [c2]Simon Geisler, Daniel Zügner, Stephan Günnemann:
Reliable Graph Neural Networks via Robust Aggregation. NeurIPS 2020 - [i1]Simon Geisler, Daniel Zügner, Stephan Günnemann:
Reliable Graph Neural Networks via Robust Aggregation. CoRR abs/2010.15651 (2020)
2010 – 2019
- 2018
- [c1]Julio De Melo Borges, Daniel Ziehr, Michael Beigl, Nélio Cacho, Allan de M. Martins
Time-Series Features for Predictive Policing. ISC2 2018: 1-8
Coauthor Index
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last updated on 2024-11-28 20:32 CET by the dblp team
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