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09/16/2023
Forward Invariance in Neural Network Controlled Systems
We present a framework based on interval analysis and monotone systems t...
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07/27/2023
Efficient Interaction-Aware Interval Analysis of Neural Network Feedback Loops
In this paper, we propose a computationally efficient framework for inte...
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06/27/2023
A Toolbox for Fast Interval Arithmetic in numpy with an Application to Formal Verification of Neural Network Controlled Systems
In this paper, we present a toolbox for interval analysis in numpy, with...
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04/07/2023
Contraction-Guided Adaptive Partitioning for Reachability Analysis of Neural Network Controlled Systems
In this paper, we present a contraction-guided adaptive partitioning alg...
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01/19/2023
Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers
This paper proposes a computationally efficient framework, based on inte...
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08/08/2022
Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach
This paper proposes a theoretical and computational framework for traini...
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04/01/2022
Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks
We use interval reachability analysis to obtain robustness guarantees fo...
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12/10/2021
Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach
Implicit neural networks are a general class of learning models that rep...
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06/06/2021
Robust Implicit Networks via Non-Euclidean Contractions
Implicit neural networks, a.k.a., deep equilibrium networks, are a class...
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05/16/2020
Topology Inference with Multivariate Cumulants: The Möbius Inference Algorithm
Many tasks regarding the monitoring, management, and design of communica...
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03/27/2020
