Quantum Robustness Verification: A Hybrid Quantum-Classical Neural Network Certification Algorithm. - Nicola Franco; Tom Wollschläger; Nicholas Gao; Jeanette Miriam Lorenz; Stephan Günnemann (QCE, 2022)

Localized Randomized Smoothing for Collective Robustness Certification. - Jan Schuchardt; Tom Wollschläger; Aleksandar Bojchevski; Stephan Günnemann (ICLR, 2023)

Uncertainty Estimation for Molecules: Desiderata and Methods. - Tom Wollschläger; Nicholas Gao; Bertrand Charpentier; Mohamed Amine Ketata; Stephan Günnemann (ICML, 2023)

Efficient MILP Decomposition in Quantum Computing for ReLU Network Robustness. - Nicola Franco; Tom Wollschläger; Benedikt Poggel; Stephan Günnemann; Jeanette Miriam Lorenz (QCE, 2023)

Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness. - Francesco Campi; Lukas Gosch; Tom Wollschläger; Yan Scholten; Stephan Günnemann (CoRR, 2023)

Uncertainty for Active Learning on Graphs. - Dominik Fuchsgruber; Tom Wollschläger; Bertrand Charpentier; Antonio Oroz; Stephan Günnemann (ICML, 2024)

Expressivity and Generalization: Fragment-Biases for Molecular GNNs. - Tom Wollschläger; Niklas Kemper; Leon Hetzel; Johanna Sommer; Stephan Günnemann (ICML, 2024)

Energy-based Epistemic Uncertainty for Graph Neural Networks. - Dominik Fuchsgruber; Tom Wollschläger; Stephan Günnemann (NeurIPS, 2024)

Certifiably Robust Encoding Schemes. - Aman Saxena; Tom Wollschläger; Nicola Franco; Jeanette Miriam Lorenz; Stephan Günnemann (QCE, 2024)

Discrete Randomized Smoothing Meets Quantum Computing. - Tom Wollschläger; Aman Saxena; Nicola Franco; Jeanette Miriam Lorenz; Stephan Günnemann (QCE, 2024)

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

Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space. - Mohamed Amine Ketata; Nicholas Gao; Johanna Sommer; Tom Wollschläger; Stephan Günnemann (ICLR, 2025)

Adversarial Alignment for LLMs Requires Simpler, Reproducible, and More Measurable Objectives. - Leo Schwinn; Yan Scholten; Tom Wollschläger; Sophie Xhonneux; Stephen Casper; Stephan Günnemann; Gauthier Gidel (CoRR, 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)

Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory. - Dominik Fuchsgruber; Tom Wollschläger; Johannes Bordne; Stephan Günnemann (CoRR, 2025)