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cs.LG2025
SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning
Tzu-Yuan Huang, Armin Lederer, Dai-Jie Wu +6
Flow matching (FM) has shown promising results in data-driven planning. However, it inherently lacks formal guarantees for ensuring state and action constraints, whose satisfaction…
cs.LG2025
Koopman-Equivariant Gaussian Processes
Petar Bevanda, Max Beier, Armin Lederer +3
Credible forecasting and representation learning of dynamical systems are of ever-increasing importance for reliable decision-making. To that end, we propose a family of Gaussian p…