| Attacking large language models with projected gradient descent S Geisler, T Wollschläger, MHI Abdalla, J Gasteiger, S Günnemann arXiv preprint arXiv:2402.09154, 2024 | 44 | 2024 |
| Quantum robustness verification: A hybrid quantum-classical neural network certification algorithm N Franco, T Wollschläger, N Gao, JM Lorenz, S Günnemann International Conference on Quantum Computing and Engineering (Talk), 142-153, 2022 | 16 | 2022 |
| Uncertainty Estimation for Molecules: Desiderata and Methods T Wollschläger, N Gao, B Charpentier, MA Ketata, S Günnemann International Conference on Machine Learning, 2023 | 11 | 2023 |
| Localized Randomized Smoothing for Collective Robustness Certification J Schuchardt*, T Wollschläger*, A Bojchevski, S Günnemann International Conference on Learning Representations (Spotlight), 2023 | 9 | 2023 |
| Efficient MILP Decomposition in Quantum Computing for ReLU Network Robustness N Franco, T Wollschläger, B Poggel, S Günnemann, JM Lorenz International Conference on Quantum Computing and Engineering, 2023 | 8 | 2023 |
| Uncertainty for Active Learning on Graphs D Fuchsgruber*, T Wollschläger*, B Charpentier, A Oroz, S Günnemann International Conference on Machine Learning, 2024 | 7 | 2024 |
| Expressivity and Generalization: Fragment-Biases for Molecular GNNs T Wollschläger*, N Kemper*, L Hetzel, J Sommer, S Günnemann International Conference on Machine Learning (Oral), 2024 | 3 | 2024 |
| Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness F Campi, L Gosch, T Wollschläger, Y Scholten, S Günnemann New Frontiers in Adversarial Machine Learning @ ICML, 2023 | 3 | 2023 |
| Certifiably Robust Encoding Schemes A Saxena*, T Wollschläger*, N Franco, JM Lorenz, S Günnemann International Conference on Quantum Computing and Engineering (Talk), 2024 | 1 | 2024 |
| Discrete Randomized Smoothing Meets Quantum Computing T Wollschläger*, A Saxena*, N Franco, JM Lorenz, S Günnemann International Conference on Quantum Computing and Engineering (Talk), 2024 | 1 | 2024 |
| Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space MA Ketata, N Gao, J Sommer, T Wollschläger, S Günnemann GRaM @ ICML 2024 (Best Paper Runner-up), 2024 | | 2024 |
| Energy-based Epistemic Uncertainty for Graph Neural Networks D Fuchsgruber, T Wollschläger, S Günnemann Neural Information Processing Systems (Spotlight), 2024 | | 2024 |
| On Quantum Computing for Neural Network Robustness Verification N Franco, T Wollschläger, N Gao, JM Lorenz, S Günnemann Workshop on Formal Verification of Machine Learning @ ICML, 2022 | | 2022 |
Stephan GünnemannProfessor of Computer Science, Technical University of MunichVerified email at in.tum.de
