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05/27/2023
Assumption Generation for the Verification of Learning-Enabled Autonomous Systems
Providing safety guarantees for autonomous systems is difficult as these...
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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...
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08/05/2022
An Overview of Structural Coverage Metrics for Testing Neural Networks
Deep neural network (DNN) models, including those used in safety-critica...
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05/08/2022
VPN: Verification of Poisoning in Neural Networks
Neural networks are successfully used in a variety of applications, many...
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01/31/2022
AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural Networks
We study backdoor poisoning attacks against image classification network...
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10/25/2021
QuantifyML: How Good is my Machine Learning Model?
The efficacy of machine learning models is typically determined by compu...
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09/23/2021
MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records
Clinical documentation can be transformed by Electronic Health Records, ...
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03/23/2021
NNrepair: Constraint-based Repair of Neural Network Classifiers
We present NNrepair, a constraint-based technique for repairing neural n...
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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...
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07/29/2020
Fast, Structured Clinical Documentation via Contextual Autocomplete
We present a system that uses a learned autocompletion mechanism to faci...
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04/17/2020
Parallelization Techniques for Verifying Neural Networks
Inspired by recent successes with parallel optimization techniques for s...
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12/01/2019
A Programmatic and Semantic Approach to Explaining and DebuggingNeural Network Based Object Detectors
Even as deep neural networks have become very effective for tasks in vis...
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09/30/2019
Hamiltonicity in Semi-Regular Tessellation Dual Graphs
This paper shows NP-completeness for finding Hamiltonian cycles in induc...
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04/29/2019
Finding Invariants in Deep Neural Networks
We present techniques for automatically inferring invariant properties o...
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10/18/2018
Compositional Verification for Autonomous Systems with Deep Learning Components
As autonomy becomes prevalent in many applications, ranging from recomme...
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07/27/2018
Symbolic Execution for Deep Neural Networks
Deep Neural Networks (DNN) are increasingly used in a variety of applica...
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10/02/2017