Search Results for author: Chelsea Sidrane

Found 6 papers, 2 papers with code

Verifying Nonlinear Neural Feedback Systems using Polyhedral Enclosures

no code implementations28 Mar 2025 Samuel I. Akinwande, Chelsea Sidrane, Mykel J. Kochenderfer, Clark Barrett

As dynamical systems equipped with neural network controllers (neural feedback systems) become increasingly prevalent, it is critical to develop methods to ensure their safe operation.

TTT: A Temporal Refinement Heuristic for Tenuously Tractable Discrete Time Reachability Problems

1 code implementation19 Jul 2024 Chelsea Sidrane, Jana Tumova

Here, we introduce an automatic framework for performing temporal refinement and we demonstrate the effectiveness of this technique on computing approximate reachable sets for nonlinear systems with neural network control policies.

Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems

no code implementations28 Sep 2022 Nicholas Rober, Sydney M. Katz, Chelsea Sidrane, Esen Yel, Michael Everett, Mykel J. Kochenderfer, Jonathan P. How

As neural networks (NNs) become more prevalent in safety-critical applications such as control of vehicles, there is a growing need to certify that systems with NN components are safe.

Verifying Inverse Model Neural Networks

no code implementations4 Feb 2022 Chelsea Sidrane, Sydney Katz, Anthony Corso, Mykel J. Kochenderfer

When the forward model that produced the observations is nonlinear and stochastic, solving the inverse problem is very challenging.

model

OVERT: An Algorithm for Safety Verification of Neural Network Control Policies for Nonlinear Systems

2 code implementations3 Aug 2021 Chelsea Sidrane, Amir Maleki, Ahmed Irfan, Mykel J. Kochenderfer

In response to this challenge, we present OVERT: a sound algorithm for safety verification of nonlinear discrete-time closed loop dynamical systems with neural network control policies.

Machine Learning for Generalizable Prediction of Flood Susceptibility

no code implementations15 Oct 2019 Chelsea Sidrane, Dylan J Fitzpatrick, Andrew Annex, Diane O'Donoghue, Yarin Gal, Piotr Biliński

In this work, we develop generalizable, multi-basin models of river flooding susceptibility using geographically-distributed data from the USGS stream gauge network.

BIG-bench Machine Learning Earth Observation +1

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