3 papers
eess.SY2025
Data-Driven Certificate Synthesis
Luke Rickard, Alessandro Abate, Kostas Margellos
We investigate the problem of verifying different properties of discrete time dynamical systems, namely, reachability, safety and reach-while-avoid. To achieve this, we adopt a dat…
eess.SY2025
Continuous-time Data-driven Barrier Certificate Synthesis
Luke Rickard, Alessandro Abate, Kostas Margellos
We consider the problem of verifying safety for continuous-time dynamical systems. Developing upon recent advancements in data-driven verification, we use only a finite number of s…
cs.LG2025
Studying Cross-cluster Modularity in Neural Networks
Satvik Golechha, Maheep Chaudhary, Joan Velja +2
An approach to improve neural network interpretability is via clusterability, i.e., splitting a model into disjoint clusters that can be studied independently. We define a measure…