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Frederik Baymler Mathiesen
Frederik Baymler Mathiesen
PhD student in probabilistic ML, Delft University of Technology
Verified email at baymler.com - Homepage
Title
Cited by
Cited by
Year
Safety certification for stochastic systems via neural barrier functions
FB Mathiesen, SC Calvert, L Laurenti
IEEE Control Systems Letters 7, 973-978, 2022
232022
Hyperverlet: A symplectic hypersolver for Hamiltonian systems
FB Mathiesen, B Yang, J Hu
Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4575-4582, 2022
72022
Inner approximations of stochastic programs for data-driven stochastic barrier function design
FB Mathiesen, L Romao, SC Calvert, A Abate, L Laurenti
2023 62nd IEEE Conference on Decision and Control (CDC), 3073-3080, 2023
22023
IntervalMDP. jl: Accelerated Value Iteration for Interval Markov Decision Processes
FB Mathiesen, M Lahijanian, L Laurenti
arXiv preprint arXiv:2401.04068, 2024
12024
Simultaneous synthesis and verification of neural control barrier functions through branch-and-bound verification-in-the-loop training
X Wang, L Knoedler, FB Mathiesen, J Alonso-Mora
arXiv preprint arXiv:2311.10438, 2023
12023
Piecewise Stochastic Barrier Functions
R Mazouz, FB Mathiesen, L Laurenti, M Lahijanian
arXiv preprint arXiv:2404.16986, 2024
2024
A Deep Learning Method for Numerically Solving Initial Value Problems of Hamiltonian Systems
A Madsen, FB Mathiesen
2021
A Flow-Efficient and Legal-by-Construction Real-Time Traffic Signal Control Platform
F Baymler Mathiesen, G Fleeman
arXiv e-prints, arXiv: 2011.00560, 2020
2020
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