research
∙
02/03/2023
Asymmetric Certified Robustness via Feature-Convex Neural Networks
Recent works have introduced input-convex neural networks (ICNNs) as lea...
share
research
∙
01/29/2023
Improving the Accuracy-Robustness Trade-off of Classifiers via Adaptive Smoothing
While it is shown in the literature that simultaneously accurate and rob...
research
∙
08/15/2022
An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models
In this discussion paper, we survey recent research surrounding robustne...
research
∙
05/31/2021
Node-Variant Graph Filters in Graph Neural Networks
Graph neural networks (GNNs) have been successfully employed in a myriad...
research
∙
01/22/2021
Partition-Based Convex Relaxations for Certifying the Robustness of ReLU Neural Networks
In this paper, we study certifying the robustness of ReLU neural network...
research
∙
10/15/2020
Certifying Neural Network Robustness to Random Input Noise from Samples
Methods to certify the robustness of neural networks in the presence of ...
research
∙
10/02/2020
Data-Driven Assessment of Deep Neural Networks with Random Input Uncertainty
When using deep neural networks to operate safety-critical systems, asse...
research
∙
04/01/2020
Tightened Convex Relaxations for Neural Network Robustness Certification
In this paper, we consider the problem of certifying the robustness of n...
research
∙
07/09/2019
