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20162023
most citedVerification for Machine Learning, Autonomy, and Neural Networks Survey

91 citations · 280 across the 22 of their papers we have counts for

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Showing 2018Show all

6 papers · 1 filter

cs.LG2018★ 10 cited

Specification-Guided Safety Verification for Feedforward Neural Networks

Weiming Xiang, Hoang-Dung Tran, Taylor T. Johnson

This paper presents a specification-guided safety verification method for feedforward neural networks with general activation functions. As such feedforward networks are memoryless…

cs.AI2018★ 91 cited

Verification for Machine Learning, Autonomy, and Neural Networks Survey

Weiming Xiang, Patrick Musau, Ayana A. Wild +5

This survey presents an overview of verification techniques for autonomous systems, with a focus on safety-critical autonomous cyber-physical systems (CPS) and subcomponents thereo…

eess.SY2018★ 42 cited

Reachability Analysis and Safety Verification for Neural Network Control Systems

Weiming Xiang, Taylor T. Johnson

Autonomous cyber-physical systems (CPS) rely on the correct operation of numerous components, with state-of-the-art methods relying on machine learning (ML) and artificial intellig…

cs.SC2018★ 2 cited

Simulation-Based Reachability Analysis for High-Index Large Linear Differential Algebraic Equations

Hoang-Dung Tran, Weiming Xiang, Nathaniel Hamilton +1

Reachability analysis is a fundamental problem for safety verification and falsification of Cyber-Physical Systems (CPS) whose dynamics follow physical laws usually represented as…

eess.SY2018★ 9 cited

Reachable Set Estimation and Safety Verification for Piecewise Linear Systems with Neural Network Controllers

Weiming Xiang, Hoang-Dung Tran, Joel A. Rosenfeld +1

In this work, the reachable set estimation and safety verification problems for a class of piecewise linear systems equipped with neural network controllers are addressed. The neur…

eess.SY2018★ 1 cited

Reachable Set Estimation and Verification for Neural Network Models of Nonlinear Dynamic Systems

Weiming Xiang, Diego Manzanas Lopez, Patrick Musau +1

Neural networks have been widely used to solve complex real-world problems. Due to the complicate, nonlinear, non-convex nature of neural networks, formal safety guarantees for the…