3 papers
cs.LG2026
Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks
David Boetius, Shahaf Bassan, Guy Katz +2
Shapley additive explanations (SHAP) are widely recognised as computationally intractable for neural networks, since they induce an exponential search space over the input features…
cs.RO2025
Stable Robot Motions on Manifolds: Learning Lyapunov-Constrained Neural Manifold ODEs
David Boetius, Abdelrahman Abdelnaby, Ashok Kumar +3
Learning stable dynamical systems from data is crucial for safe and reliable robot motion planning and control. However, extending stability guarantees to trajectories defined on R…
cs.LG2025
Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound
David Boetius, Stefan Leue, Tobias Sutter
Probabilistic verification problems of neural networks are concerned with formally analysing the output distribution of a neural network under a probability distribution of the inp…