research
∙
06/23/2023
QNNRepair: Quantized Neural Network Repair
We present QNNRepair, the first method in the literature for repairing q...
share
research
∙
05/24/2023
A New Era in Software Security: Towards Self-Healing Software via Large Language Models and Formal Verification
In this paper we present a novel solution that combines the capabilities...
research
∙
11/24/2022
AIREPAIR: A Repair Platform for Neural Networks
We present AIREPAIR, a platform for repairing neural networks. It featur...
research
∙
11/23/2022
Safety Analysis of Autonomous Driving Systems Based on Model Learning
We present a practical verification method for safety analysis of the au...
research
∙
08/05/2022
An Overview of Structural Coverage Metrics for Testing Neural Networks
Deep neural network (DNN) models, including those used in safety-critica...
research
∙
05/25/2022
VeriFi: Towards Verifiable Federated Unlearning
Federated learning (FL) is a collaborative learning paradigm where parti...
research
∙
05/08/2022
VPN: Verification of Poisoning in Neural Networks
Neural networks are successfully used in a variety of applications, many...
research
∙
01/31/2022
AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural Networks
We study backdoor poisoning attacks against image classification network...
research
∙
12/10/2021
Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models
Deep learning (DL) models, especially those large-scale and high-perform...
research
∙
08/03/2021
Tutorials on Testing Neural Networks
Deep learning achieves remarkable performance on pattern recognition, bu...
research
∙
03/23/2021
NNrepair: Constraint-based Repair of Neural Network Classifiers
We present NNrepair, a constraint-based technique for repairing neural n...
research
∙
03/05/2021
Compositional Explanations for Image Classifiers
Existing algorithms for explaining the output of image classifiers perfo...
research
∙
02/27/2021
NEUROSPF: A tool for the Symbolic Analysis of Neural Networks
This paper presents NEUROSPF, a tool for the symbolic analysis of neural...
research
∙
02/11/2021
RobOT: Robustness-Oriented Testing for Deep Learning Systems
Recently, there has been a significant growth of interest in applying so...
research
∙
10/16/2020
Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems for Robotics
This paper presents a formal verification guided approach for a principl...
research
∙
08/31/2020
Ranking Policy Decisions
Policies trained via Reinforcement Learning (RL) are often needlessly co...
research
∙
02/06/2020
Reliability Validation of Learning Enabled Vehicle Tracking
This paper studies the reliability of a real-world learning-enabled syst...
research
∙
11/05/2019
Test Metrics for Recurrent Neural Networks
Recurrent neural networks (RNNs) have been applied to a broad range of a...
research
∙
08/06/2019
Explaining Deep Neural Networks Using Spectrum-Based Fault Localization
Deep neural networks (DNNs) increasingly replace traditionally developed...
research
∙
06/20/2019
testRNN: Coverage-guided Testing on Recurrent Neural Networks
Recurrent neural networks (RNNs) have been widely applied to various seq...
research
∙
12/18/2018
Safety and Trustworthiness of Deep Neural Networks: A Survey
In the past few years, significant progress has been made on deep neural...
research
∙
04/30/2018
Concolic Testing for Deep Neural Networks
Concolic testing alternates between CONCrete program execution and symbO...
research
∙
04/16/2018
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for L0 Norm
Deployment of deep neural networks (DNNs) in safety or security-critical...
research
∙
03/10/2018
Testing Deep Neural Networks
Deep neural networks (DNNs) have a wide range of applications, and softw...
research
∙
12/07/2015
Parallel and sequential reclaiming in multicore real-time global scheduling
When integrating hard, soft and non-real-time tasks in general purpose o...
research
∙
04/01/2014
Toward Parametric Timed Interfaces for Real-Time Components
We propose here a framework to model real-time components consisting of ...
research
∙
02/06/2013