67 citations · 173 across the 30 of their papers we have counts for
5 papers · 1 filter
GoTube: Scalable Stochastic Verification of Continuous-Depth Models
Sophie Gruenbacher, Mathias Lechner, Ramin Hasani +4
We introduce a new stochastic verification algorithm that formally quantifies the behavioral robustness of any time-continuous process formulated as a continuous-depth model. Our a…
On The Verification of Neural ODEs with Stochastic Guarantees
Sophie Gruenbacher, Ramin Hasani, Mathias Lechner +3
We show that Neural ODEs, an emerging class of time-continuous neural networks, can be verified by solving a set of global-optimization problems. For this purpose, we introduce Sto…
MPC-guided Imitation Learning of Neural Network Policies for the Artificial Pancreas
Hongkai Chen, Nicola Paoletti, Scott A. Smolka +1
Even though model predictive control (MPC) is currently the main algorithm for insulin control in the artificial pancreas (AP), it usually requires complex online optimizations, wh…
Neural State Classification for Hybrid Systems
Dung Phan, Nicola Paoletti, Timothy Zhang +3
We introduce the State Classification Problem (SCP) for hybrid systems, and present Neural State Classification (NSC) as an efficient solution technique. SCP generalizes the model…
How to Learn a Model Checker
Dung Phan, Radu Grosu, Nicola Paoletti +2
We show how machine-learning techniques, particularly neural networks, offer a very effective and highly efficient solution to the approximate model-checking problem for continuous…