Reachability analysis of a general class of neural ordinary differential equations

DOI10.1007/978-3-031-15839-1_15OpenAlexW4293399525MaRDI QIDQ2112130

Diego Manzanas Lopez, Patrick Musau, Nathaniel P. Hamilton, Taylor T. Johnson

Publication date: 18 January 2023

Full work available at URL: https://arxiv.org/abs/2207.06531

Mathematics Subject Classification ID

Theory of computing (68Qxx)

Related Items (1)

NNVODE

Uses Software

• SpaceEx
• Flow*
• CORA
• JuliaReach
• Reluplex
• Marabou
• NNV
• NeuralCDE
• torchcde
• Diffrax
• Verisig
• GoTube
• ANODE
• nnenum
• ReachNN

Cites Work

• Verisig 2.0: verification of neural network controllers using Taylor model preconditioning
• Reachability analysis of nonlinear systems using hybridization and dynamics scaling
• Reluplex: an efficient SMT solver for verifying deep neural networks
• Simulation-equivalent reachability of large linear systems with inputs
• Verification of deep convolutional neural networks using ImageStars
• Reachability analysis of nonlinear systems using conservative polynomialization and non-convex sets
• Verification of Hybrid Systems
• Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks
• Case study
• JuliaReach
• Reachability analysis for neural feedback systems using regressive polynomial rule inference
• Verisig

This page was built for publication: Reachability analysis of a general class of neural ordinary differential equations