Search Results for author:
Found 3 papers, 2 papers with code
Reach-avoid Analysis for Sampled-data Systems with Measurement Uncertainties
Digital control has become increasingly prevalent in modern systems, making continuous-time plants controlled by discrete-time (digital) controllers ubiquitous and crucial across industries, including aerospace, automotive, and manufacturing.
Verifying Safety of Neural Networks from Topological Perspectives
Moreover, for NNs that do not feature these properties with respect to the input set, we explore subsets of the input set for establishing the local homeomorphism property and then abandon these subsets for reachability computations.
Safety Verification for Neural Networks Based on Set-boundary Analysis
The homeomorphism property exists in some widely used NNs such as invertible NNs.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
