Corina S. Pasareanu | DeepAI

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∙ 02/06/2023

Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study

Deep neural networks (DNNs) are increasingly used in safety-critical aut...

0 Corina S. Pasareanu, et al. ∙

∙ 08/05/2022

An Overview of Structural Coverage Metrics for Testing Neural Networks

Deep neural network (DNN) models, including those used in safety-critica...

0 Muhammad Usman, et al. ∙

∙ 05/08/2022

VPN: Verification of Poisoning in Neural Networks

Neural networks are successfully used in a variety of applications, many...

0 Youcheng Sun, et al. ∙

∙ 01/31/2022

AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural Networks

We study backdoor poisoning attacks against image classification network...

0 Muhammad Usman, et al. ∙

∙ 10/25/2021

QuantifyML: How Good is my Machine Learning Model?

The efficacy of machine learning models is typically determined by compu...

0 Muhammad Usman, et al. ∙

∙ 03/02/2021

DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers

We introduce DeepCert, a tool-supported method for verifying the robustn...

0 Colin Paterson, et al. ∙

∙ 04/29/2019

Finding Invariants in Deep Neural Networks

We present techniques for automatically inferring invariant properties o...

0 Divya Gopinath, et al. ∙

∙ 11/16/2018

DifFuzz: Differential Fuzzing for Side-Channel Analysis

Side-channel attacks allow an adversary to uncover secret program data b...

0 Shirin Nilizadeh, et al. ∙

∙ 10/18/2018

Compositional Verification for Autonomous Systems with Deep Learning Components

As autonomy becomes prevalent in many applications, ranging from recomme...

0 Corina S. Pasareanu, et al. ∙

∙ 07/27/2018

Symbolic Execution for Deep Neural Networks

Deep Neural Networks (DNN) are increasingly used in a variety of applica...

0 Divya Gopinath, et al. ∙

∙ 06/08/2018

Badger: Complexity Analysis with Fuzzing and Symbolic Execution

Hybrid testing approaches that involve fuzz testing and symbolic executi...

0 Yannic Noller, et al. ∙

∙ 10/02/2017

DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks

Deep neural networks have become widely used, obtaining remarkable resul...

0 Divya Gopinath, et al. ∙

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