We establish a layer-wise parameterization for 1D convolutional neural
n...
This paper introduces a novel representation of convolutional Neural Net...
In this work, we propose a dissipativity-based method for Lipschitz cons...
The security of public-key cryptosystems relies on computationally hard
...
This paper is concerned with the training of neural networks (NNs) under...
We consider the problem of computing reachable sets directly from noisy ...
In this paper, we analyze the stability of feedback interconnections of ...
Encrypted control systems allow to evaluate feedback laws on external se...
In this paper, we present a method to analyze local and global stability...
In this paper, we propose a data-driven reachability analysis approach f...
Due to their susceptibility to adversarial perturbations, neural network...
This paper considers the stability analysis for nonlinear sampled-data
s...
Fast feedback control and safety guarantees are essential in modern robo...
A supervised learning framework is proposed to approximate a model predi...