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A review of safe reinforcement learning: Methods, theory and applications
Reinforcement Learning (RL) has achieved tremendous success in many complex decision-
making tasks. However, safety concerns are raised during deploying RL in real-world …
making tasks. However, safety concerns are raised during deploying RL in real-world …
Set propagation techniques for reachability analysis
Reachability analysis consists in computing the set of states that are reachable by a
dynamical system from all initial states and for all admissible inputs and parameters. It is a …
dynamical system from all initial states and for all admissible inputs and parameters. It is a …
NNV: the neural network verification tool for deep neural networks and learning-enabled cyber-physical systems
This paper presents the Neural Network Verification (NNV) software tool, a set-based
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
NNV 2.0: the neural network verification tool
This manuscript presents the updated version of the Neural Network Verification (NNV) tool.
NNV is a formal verification software tool for deep learning models and cyber-physical …
NNV is a formal verification software tool for deep learning models and cyber-physical …
Verification of deep convolutional neural networks using imagestars
Abstract Convolutional Neural Networks (CNN) have redefined state-of-the-art in many real-
world applications, such as facial recognition, image classification, human pose estimation …
world applications, such as facial recognition, image classification, human pose estimation …
Deep reinforcement learning verification: a survey
Deep reinforcement learning (DRL) has proven capable of superhuman performance on
many complex tasks. To achieve this success, DRL algorithms train a decision-making agent …
many complex tasks. To achieve this success, DRL algorithms train a decision-making agent …
The fourth international verification of neural networks competition (vnn-comp 2023): Summary and results
This report summarizes the 4th International Verification of Neural Networks Competition
(VNN-COMP 2023), held as a part of the 6th Workshop on Formal Methods for ML-Enabled …
(VNN-COMP 2023), held as a part of the 6th Workshop on Formal Methods for ML-Enabled …
Verisig 2.0: Verification of neural network controllers using taylor model preconditioning
Abstract This paper presents Verisig 2.0, a verification tool for closed-loop systems with
neural network (NN) controllers. We focus on NNs with tanh/sigmoid activations and develop …
neural network (NN) controllers. We focus on NNs with tanh/sigmoid activations and develop …
Efficient neural network verification via adaptive refinement and adversarial search
We propose a novel verification method for high-dimensional feed-forward neural networks
governed by ReLU, Sigmoid and Tanh activation functions. We show that the method is …
governed by ReLU, Sigmoid and Tanh activation functions. We show that the method is …
Formal certification methods for automated vehicle safety assessment
Challenges related to automated driving are no longer focused on just the construction of
such automated vehicles (AVs) but also on assuring the safety of operation. Recent …
such automated vehicles (AVs) but also on assuring the safety of operation. Recent …