Patricia Pauli

According to our database, Patricia Pauli authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

LipKernel: Lipschitz-Bounded Convolutional Neural Networks via Dissipative Layers.

Patricia Pauli, Ruigang Wang, Ian R. Manchester, Frank Allgöwer

CoRR, 2024

Lipschitz constant estimation for general neural network architectures using control tools.

Patricia Pauli, Dennis Gramlich, Frank Allgöwer

CoRR, 2024

State space representations of the Roesser type for convolutional layers.

Patricia Pauli, Dennis Gramlich, Frank Allgöwer

CoRR, 2024

Learning soft constrained MPC value functions: Efficient MPC design and implementation providing stability and safety guarantees.

Nicolas Chatzikiriakos, Kim Peter Wabersich, Felix Berkel, Patricia Pauli, Andrea Iannelli

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations.

Patricia Pauli, Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Convolutional Neural Networks as 2-D systems.

Dennis Gramlich, Patricia Pauli, Carsten W. Scherer, Frank Allgöwer, Christian Ebenbauer

CoRR, 2023

Lipschitz constant estimation for 1D convolutional neural networks.

Patricia Pauli, Dennis Gramlich, Frank Allgöwer

Proceedings of the Learning for Dynamics and Control Conference, 2023

Lipschitz-Bounded 1D Convolutional Neural Networks using the Cayley Transform and the Controllability Gramian.

Patricia Pauli, Ruigang Wang, Ian R. Manchester, Frank Allgöwer

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Training Robust Neural Networks Using Lipschitz Bounds.

Patricia Pauli, Anne Koch, Julian Berberich, Paul Kohler, Frank Allgöwer

IEEE Control. Syst. Lett., 2022

Bounding the difference between model predictive control and neural networks.

Ross Drummond, Stephen R. Duncan, Matthew C. Turner, Patricia Pauli, Frank Allgöwer

CoRR, 2022

Robustness analysis and training of recurrent neural networks using dissipativity theory.

Patricia Pauli, Julian Berberich, Frank Allgöwer

Autom., 2022

Bounding the Difference Between Model Predictive Control and Neural Networks.

Ross Drummond, Stephen Duncan, Mathew Turner, Patricia Pauli, Frank Allgöwer

Proceedings of the Learning for Dynamics and Control Conference, 2022

Neural network training under semidefinite constraints.

Patricia Pauli, Niklas Funcke, Dennis Gramlich, Mohamed Amine Msalmi, Frank Allgöwer

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Robust and optimal predictive control of the COVID-19 outbreak.

Johannes Köhler, Lukas Schwenkel, Anne Koch, Julian Berberich, Patricia Pauli, Frank Allgöwer

Annu. Rev. Control., 2021

Offset-free setpoint tracking using neural network controllers.

Patricia Pauli, Johannes Köhler, Julian Berberich, Anne Koch, Frank Allgöwer

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliers.

Patricia Pauli, Dennis Gramlich, Julian Berberich, Frank Allgöwer

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Training robust neural networks using Lipschitz bounds.

Patricia Pauli, Anne Koch, Julian Berberich, Frank Allgöwer

CoRR, 2020

2019

Optimal Delay Assignment in Delay-Aware Control of Cyber-Physical Systems: A Machine Learning Approach.

Patricia Pauli, Seyed Mehran Dibaji, Anuradha M. Annaswamy, Aranya Chakrabortty

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

The Sharing Economy for Residential Solar Generation.

Rodrigo Henriquez-Auba, Patricia Pauli, Dileep M. Kalathil, Duncan S. Callaway, Kameshwar Poolla

Proceedings of the 57th IEEE Conference on Decision and Control, 2018