59 citations · 183 across the 18 of their papers we have counts for
21 papers
Fighting AI with AI: Leveraging Foundation Models for Assuring AI-Enabled Safety-Critical Systems
Anastasia Mavridou, Divya Gopinath, Corina S. Păsăreanu
The integration of AI components, particularly Deep Neural Networks (DNNs), into safety-critical systems such as aerospace and autonomous vehicles presents fundamental challenges f…
Prophecy: Inferring Formal Properties from Neuron Activations
Divya Gopinath, Corina S. Pasareanu, Muhammad Usman
We present Prophecy, a tool for automatically inferring formal properties of feed-forward neural networks. Prophecy is based on the observation that a significant part of the logic…
Evaluating Deep Neural Networks in Deployment (A Comparative and Replicability Study)
Eduard Pinconschi, Divya Gopinath, Rui Abreu +1
As deep neural networks (DNNs) are increasingly used in safety-critical applications, there is a growing concern for their reliability. Even highly trained, high-performant network…
Assumption Generation for the Verification of Learning-Enabled Autonomous Systems
Corina Pasareanu, Ravi Mangal, Divya Gopinath +1
Providing safety guarantees for autonomous systems is difficult as these systems operate in complex environments that require the use of learning-enabled components, such as deep n…
Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study
Corina S. Pasareanu, Ravi Mangal, Divya Gopinath +4
Deep neural networks (DNNs) are increasingly used in safety-critical autonomous systems as perception components processing high-dimensional image data. Formal analysis of these sy…
An Overview of Structural Coverage Metrics for Testing Neural Networks
Muhammad Usman, Youcheng Sun, Divya Gopinath +3
Deep neural network (DNN) models, including those used in safety-critical domains, need to be thoroughly tested to ensure that they can reliably perform well in different scenarios…
VPN: Verification of Poisoning in Neural Networks
Youcheng Sun, Muhammad Usman, Divya Gopinath +1
Neural networks are successfully used in a variety of applications, many of them having safety and security concerns. As a result researchers have proposed formal verification tech…
AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural Networks
Muhammad Usman, Youcheng Sun, Divya Gopinath +1
We study backdoor poisoning attacks against image classification networks, whereby an attacker inserts a trigger into a subset of the training data, in such a way that at test time…
QuantifyML: How Good is my Machine Learning Model?
Muhammad Usman, Divya Gopinath, Corina S. Păsăreanu
The efficacy of machine learning models is typically determined by computing their accuracy on test data sets. However, this may often be misleading, since the test data may not be…
MedKnowts: Unified Documentation and Information Retrieval for Electronic Health Records
Luke Murray, Divya Gopinath, Monica Agrawal +3
Clinical documentation can be transformed by Electronic Health Records, yet the documentation process is still a tedious, time-consuming, and error-prone process. Clinicians are fa…
NNrepair: Constraint-based Repair of Neural Network Classifiers
Muhammad Usman, Divya Gopinath, Youcheng Sun +2
We present NNrepair, a constraint-based technique for repairing neural network classifiers. The technique aims to fix the logic of the network at an intermediate layer or at the la…
NEUROSPF: A tool for the Symbolic Analysis of Neural Networks
Muhammad Usman, Yannic Noller, Corina Pasareanu +2
This paper presents NEUROSPF, a tool for the symbolic analysis of neural networks. Given a trained neural network model, the tool extracts the architecture and model parameters and…
Fast, Structured Clinical Documentation via Contextual Autocomplete
Divya Gopinath, Monica Agrawal, Luke Murray +3
We present a system that uses a learned autocompletion mechanism to facilitate rapid creation of semi-structured clinical documentation. We dynamically suggest relevant clinical co…
Parallelization Techniques for Verifying Neural Networks
Haoze Wu, Alex Ozdemir, Aleksandar Zeljić +7
Inspired by recent successes with parallel optimization techniques for solving Boolean satisfiability, we investigate a set of strategies and heuristics that aim to leverage parall…
A Programmatic and Semantic Approach to Explaining and DebuggingNeural Network Based Object Detectors
Edward Kim, Divya Gopinath, Corina Pasareanu +1
Even as deep neural networks have become very effective for tasks in vision and perception, it remains difficult to explain and debug their behavior. In this paper, we present a pr…
Hamiltonicity in Semi-Regular Tessellation Dual Graphs
Divya Gopinath, Rohan Kodialam, Kevin Lu +2
This paper shows NP-completeness for finding Hamiltonian cycles in induced subgraphs of the dual graphs of semi-regular tessilations. It also shows NP-hardness for a new, wide clas…
Property Inference for Deep Neural Networks
Divya Gopinath, Hayes Converse, Corina S. Pasareanu +1
We present techniques for automatically inferring formal properties of feed-forward neural networks. We observe that a significant part (if not all) of the logic of feed forward ne…
Compositional Verification for Autonomous Systems with Deep Learning Components
Corina S. Pasareanu, Divya Gopinath, Huafeng Yu
As autonomy becomes prevalent in many applications, ranging from recommendation systems to fully autonomous vehicles, there is an increased need to provide safety guarantees for su…
Symbolic Execution for Deep Neural Networks
Divya Gopinath, Kaiyuan Wang, Mengshi Zhang +2
Deep Neural Networks (DNN) are increasingly used in a variety of applications, many of them with substantial safety and security concerns. This paper introduces DeepCheck, a new ap…
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks
Divya Gopinath, Guy Katz, Corina S. Pasareanu +1
Deep neural networks have become widely used, obtaining remarkable results in domains such as computer vision, speech recognition, natural language processing, audio recognition, s…
GUI system for Elders/Patients in Intensive Care
J. L. Raheja, Dhiraj, D. Gopinath +1
In the old age, few people need special care if they are suffering from specific diseases as they can get stroke while they are in normal life routine. Also patients of any age, wh…