Takip et
Simon Geisler
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Robustness of graph neural networks at scale
S Geisler, T Schmidt, H Şirin, D Zügner, A Bojchevski, S Günnemann
Advances in Neural Information Processing Systems 34, 7637-7649, 2021
1452021
Reliable Graph Neural Networks via Robust Aggregation
S Geisler, D Zügner, S Günnemann
Advances in Neural Information Processing Systems 33, 2020
942020
Graph posterior network: Bayesian predictive uncertainty for node classification
M Stadler, B Charpentier, S Geisler, D Zügner, S Günnemann
Advances in Neural Information Processing Systems 34, 18033-18048, 2021
872021
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions
B Charpentier, O Borchert, D Zügner, S Geisler, S Günnemann
International Conference on Learning Representations (ICLR), 2022
77*2022
Are Defenses for Graph Neural Networks Robust?
S Geisler*, F Mujkanovic*, S Günnemann, A Bojchevski
Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022
74*2022
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness
S Geisler, J Sommer, J Schuchardt, A Bojchevski, S Günnemann
International Conference on Learning Representations (ICLR), 2022
472022
Attacking Large Language Models with Projected Gradient Descent
S Geisler, T Wollschläger, MHI Abdalla, J Gasteiger, S Günnemann
arXiv preprint arXiv:2402.09154, 2024
442024
Transformers Meet Directed Graphs
S Geisler, Y Li, D Mankowitz, AT Cemgil, S Günnemann, C Paduraru
International Conference on Machine Learning (ICML), 2023
402023
Winning the Lottery Ahead of Time: Efficient Early Network Pruning
J Rachwan, D Zügner, B Charpentier, S Geisler, M Ayle, S Günnemann
International Conference on Machine Learning, 18293-18309, 2022
332022
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
S Geisler*, L Gosch*, D Sturm*, B Charpentier, D Zügner, S Günnemann
Thirty-seventh Conference on Neural Information Processing Systems, 2023
32*2023
Revisiting Robustness in Graph Machine Learning
L Gosch, D Sturm, S Geisler, S Günnemann
International Conference on Learning Representations (ICLR), 2023
262023
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks
Y Scholten, J Schuchardt, S Geisler, A Bojchevski, S Günnemann
Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022
222022
Time-series features for predictive policing
J Borges, D Ziehr, M Beigl, N Cacho, A Martins, A Araujo, L Bezerra, ...
2018 IEEE international smart cities conference (ISC2), 1-8, 2018
172018
Method and control and detection unit for checking the plausibility of a wrong-way driving incident of a motor vehicle
C Jeschke, C Braeuchle, S Geisler
US Patent 9,786,166, 2017
122017
Method, device and system for wrong-way driver detection
S Geisler
US Patent 10,916,124, 2021
72021
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning
J Feng, J Lee, S Geisler, S Günnemann, R Triebel
7th Annual Conference on Robot Learning, 2023
62023
Attacking Graph Neural Networks at Scale
S Geisler, D Zügner, A Bojchevski, S Günnemann
DLG workshop @ AAAI, 2021
62021
Spatio-Spectral Graph Neural Networks
S Geisler, A Kosmala, D Herbst, S Günnemann
arXiv preprint arXiv:2405.19121, 2024
52024
On the Robustness and Anomaly Detection of Sparse Neural Networks
M Ayle, B Charpentier, J Rachwan, D Zügner, S Geisler, S Günnemann
arXiv preprint arXiv:2207.04227, 2022
52022
Method for determining a coefficient of friction for a contact between a tire of a vehicle and a roadway, and method for controlling a vehicle function of a vehicle
C Lellmann, S Geisler
US Patent App. 16/100,390, 2019
52019
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Makaleler 1–20