Designing neural controllers with optimality and stability guarantees by learning input-output dissipativity
Automatica 191, 113120, 2026
Archive
Publications
Learning Koopman Representations with Controllability Guarantees
The Fourteenth International Conference on Learning Representations, 2026
Scholar Published
Data-enabled predictive control for nonlinear systems based on a Koopman bilinear realization
2025 IEEE 64th Conference on Decision and Control (CDC), 6498-6503, 2025
Scholar Published
NLBAC: A neural ODE-based algorithm for state-wise stable and safe reinforcement learning
Neurocomputing, Volume 638, Article 130041, 2025
Opt-ODENet: Neural ODE controller design with differentiable optimization layers for safety and stability
Proceedings of the 7th Annual Learning for Dynamics and Control Conference, PMLR 283:1217–1229, 2025
How deep do we need: Accelerating training and inference of neural ODEs via control perspective
Proceedings of the 41st International Conference on Machine Learning 235 …, 2024
Learning robust state observers using neural odes
Learning for Dynamics and Control Conference, 208-219, 2023
Towards Optimal Network Depths: Control-Inspired Acceleration of Training and Inference in Neural ODEs
The Symbiosis of Deep Learning and Differential Equations III, 2023
Optimal control of a growth/consumption model
Optimal Control Applications and Methods 42 (6), 1672-1688, 2021