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06/27/2023
Verifying Safety of Neural Networks from Topological Perspectives
Neural networks (NNs) are increasingly applied in safety-critical system...
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05/05/2023
Repairing Deep Neural Networks Based on Behavior Imitation
The increasing use of deep neural networks (DNNs) in safety-critical sys...
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04/17/2023
Scenario Approach for Parametric Markov Models
In this paper, we propose an approximating framework for analyzing param...
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12/02/2022
Credit Assignment for Trained Neural Networks Based on Koopman Operator Theory
Credit assignment problem of neural networks refers to evaluating the cr...
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10/09/2022
Safety Verification for Neural Networks Based on Set-boundary Analysis
Neural networks (NNs) are increasingly applied in safety-critical system...
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09/20/2022
Encoding inductive invariants as barrier certificates: synthesis via difference-of-convex programming
A barrier certificate often serves as an inductive invariant that isolat...
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06/05/2021
Ensemble Defense with Data Diversity: Weak Correlation Implies Strong Robustness
In this paper, we propose a framework of filter-based ensemble of deep n...
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05/29/2021
Synthesizing Invariant Barrier Certificates via Difference-of-Convex Programming
A barrier certificate often serves as an inductive invariant that isolat...
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01/25/2021
Probabilistic Robustness Analysis for DNNs based on PAC Learning
This paper proposes a black box based approach for analysing deep neural...
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10/15/2020
Improving Neural Network Verification through Spurious Region Guided Refinement
We propose a spurious region guided refinement approach for robustness v...
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07/17/2020
PAC Model Checking of Black-Box Continuous-Time Dynamical Systems
In this paper we present a novel model checking approach to finite-time ...
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11/28/2018
