Search Results for author:
Found 3 papers, 0 papers with code
Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures
Recent model inversion attack algorithms permit adversaries to reconstruct a neural network's private training data just by repeatedly querying the network and inspecting its outputs.
How Robust Are Energy-Based Models Trained With Equilibrium Propagation?
Deep neural networks (DNNs) are easily fooled by adversarial perturbations that are imperceptible to humans.
A Systematic Comparison of Deep Learning Architectures in an Autonomous Vehicle
To date, however, there has been no systematic comparison of how different deep learning architectures perform at such tasks, or an attempt to determine a correlation between classification performance and performance in an actual vehicle, a potentially critical factor in developing self-driving systems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
