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Patricia Pauli
Patricia Pauli
Research Assistant, University of Stuttgart
Verified email at ist.uni-stuttgart.de - Homepage
Title
Cited by
Cited by
Year
Robust and optimal predictive control of the COVID-19 outbreak
J K÷hler, L Schwenkel, A Koch, J Berberich, P Pauli, F Allg÷wer
Annual Reviews in Control 51, 525-539, 2021
1522021
Training robust neural networks using Lipschitz bounds
P Pauli, A Koch, J Berberich, P Kohler, F Allg÷wer
IEEE Control Systems Letters 6, 121-126, 2021
1502021
Offset-free setpoint tracking using neural network controllers
P Pauli, J K÷hler, J Berberich, A Koch, F Allg÷wer
Learning for Dynamics and Control, 992-1003, 2021
202021
Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliers
P Pauli, D Gramlich, J Berberich, F Allg÷wer
2021 60th IEEE Conference on Decision and Control (CDC), 3611-3618, 2021
192021
Sharing economy and optimal investment decisions for distributed solar generation
R Henriquez-Auba, P Hidalgo-Gonzalez, P Pauli, D Kalathil, DS Callaway, ...
Applied Energy 294, 117029, 2021
172021
The sharing economy for residential solar generation
R Henriquez-Auba, P Pauli, D Kalathil, DS Callaway, K Poolla
2018 IEEE Conference on Decision and Control (CDC), 7322-7329, 2018
152018
Smartphone apps for learning progress and course revision
P Pauli, A Koch, F Allg÷wer
IFAC-PapersOnLine 53 (2), 17368-17373, 2020
132020
Neural network training under semidefinite constraints
P Pauli, N Funcke, D Gramlich, MA Msalmi, F Allg÷wer
2022 IEEE 61st Conference on Decision and Control (CDC), 2731-2736, 2022
122022
Lipschitz constant estimation for 1D convolutional neural networks
P Pauli, D Gramlich, F Allg÷wer
Learning for Dynamics and Control Conference, 1321-1332, 2023
92023
Convolutional neural networks as 2-D systems
D Gramlich, P Pauli, CW Scherer, F Allg÷wer, C Ebenbauer
arXiv preprint arXiv:2303.03042, 2023
82023
Bounding the difference between model predictive control and neural networks
R Drummond, S Duncan, M Turner, P Pauli, F Allgower
Learning for Dynamics and Control Conference, 817-829, 2022
72022
Lipschitz-bounded 1D convolutional neural networks using the Cayley transform and the controllability Gramian
P Pauli, R Wang, IR Manchester, F Allg÷wer
arXiv preprint arXiv:2303.11835, 2023
52023
Robustness analysis and training of recurrent neural networks using dissipativity theory
P Pauli, J Berberich, F Allg÷wer
at-Automatisierungstechnik 70 (8), 730-739, 2022
52022
Facilitating learning progress in a first control course via Matlab apps
A Koch, M Lorenzen, P Pauli, F Allg÷wer
IFAC-PapersOnLine 53 (2), 17356-17361, 2020
52020
Optimal delay assignment in delay-aware control of cyber-physical systems: A machine learning approach
P Pauli, SM Dibaji, AM Annaswamy, A Chakrabortty
2019 IEEE 58th Conference on Decision and Control (CDC), 4583-4588, 2019
12019
Facilitating learning progress in a first control course via Matlab Apps
A Romer, M Lorenzen, P Pauli, F Allg÷wer
Proc. 21st IFAC World Congress. Submitted- preprint online https://www. istá…, 2019
12019
Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations
P Pauli, A Havens, A Araujo, S Garg, F Khorrami, F Allg÷wer, B Hu
arXiv preprint arXiv:2401.14033, 2024
2024
Learning Soft Constrained MPC Value Functions: Efficient MPC Design and Implementation providing Stability and Safety Guarantees
N Chatzikiriakos, KP Wabersich, F Berkel, P Pauli, A Iannelli
arXiv preprint arXiv:2401.07780, 2024
2024
Lipschitz-bounded convolutional neural networks
P Pauli, F Allg÷wer
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Articles 1–19