Search Results for author: Marcelo Forets

Found 6 papers, 3 papers with code

The inverse problem for neural networks

1 code implementation27 Aug 2023 Marcelo Forets, Christian Schilling

We study the problem of computing the preimage of a set under a neural network with piecewise-affine activation functions.

Verification of Neural-Network Control Systems by Integrating Taylor Models and Zonotopes

1 code implementation16 Dec 2021 Christian Schilling, Marcelo Forets, Sebastian Guadalupe

When considering dynamical systems and neural networks in isolation, there exist precise approaches for that task based on set representations respectively called Taylor models and zonotopes.

Efficient reachability analysis of parametric linear hybrid systems with time-triggered transitions

1 code implementation22 Jun 2020 Marcelo Forets, Daniel Freire, Christian Schilling

In this paper we present an approach based on conservative set-based enclosure of the dynamics that can handle systems with uncertain parameters and inputs, where the uncertainties are bound to given intervals.

Reachability analysis of linear hybrid systems via block decomposition

no code implementations7 May 2019 Sergiy Bogomolov, Marcelo Forets, Goran Frehse, Kostiantyn Potomkin, Christian Schilling

Reachability analysis aims at identifying states reachable by a system within a given time horizon.

Systems and Control Dynamical Systems Optimization and Control

JuliaReach: a Toolbox for Set-Based Reachability

no code implementations30 Jan 2019 Sergiy Bogomolov, Marcelo Forets, Goran Frehse, Kostiantyn Potomkin, Christian Schilling

We present JuliaReach, a toolbox for set-based reachability analysis of dynamical systems.

Systems and Control Dynamical Systems

Reach Set Approximation through Decomposition with Low-dimensional Sets and High-dimensional Matrices

no code implementations29 Jan 2018 Sergiy Bogomolov, Marcelo Forets, Goran Frehse, Andreas Podelski, Christian Schilling, Frédéric Viry

Approximating the set of reachable states of a dynamical system is an algorithmic yet mathematically rigorous way to reason about its safety.

Systems and Control Dynamical Systems

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