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 …
Overt: An algorithm for safety verification of neural network control policies for nonlinear systems
Deep learning methods can be used to produce control policies, but certifying their safety is
challenging. The resulting networks are nonlinear and often very large. In response to this …
challenging. The resulting networks are nonlinear and often very large. In response to this …
Verification of neural-network control systems by integrating Taylor models and zonotopes
C Schilling, M Forets, S Guadalupe - … of the AAAI Conference on Artificial …, 2022 - ojs.aaai.org
We study the verification problem for closed-loop dynamical systems with neural-network
controllers (NNCS). This problem is commonly reduced to computing the set of reachable …
controllers (NNCS). This problem is commonly reduced to computing the set of reachable …
ARCH-COMP23 category report: Artificial intelligence and neural network control systems (AINNCS) for continuous and hybrid systems plants
This report presents the results of a friendly competition for formal verification of continuous
and hybrid systems with artificial intelligence (AI) components. Specifically, machine …
and hybrid systems with artificial intelligence (AI) components. Specifically, machine …
Tight neural network verification via semidefinite relaxations and linear reformulations
We present a novel semidefinite programming (SDP) relaxation that enables tight and
efficient verification of neural networks. The tightness is achieved by combining SDP …
efficient verification of neural networks. The tightness is achieved by combining SDP …
[PDF][PDF] Verifying strategic abilities of neural-symbolic multi-agent systems
We investigate the problem of verifying the strategic properties of multi-agent systems
equipped with machine learningbased perception units. We introduce a novel model of …
equipped with machine learningbased perception units. We introduce a novel model of …
Evaluation of neural network verification methods for air-to-air collision avoidance
Neural network approximations have become attractive to compress data for automation and
autonomy algorithms for use on storage-limited and processing-limited aerospace …
autonomy algorithms for use on storage-limited and processing-limited aerospace …
ARCH-COMP20 category report: artificial intelligence and neural network control systems (AINNCS) for continuous and hybrid systems plants
This report presents the results of a friendly competition for formal verification of continuous
and hybrid systems with artificial intelligence (AI) components. Specifically, machine …
and hybrid systems with artificial intelligence (AI) components. Specifically, machine …
Knowledge augmented machine learning with applications in autonomous driving: A survey
The availability of representative datasets is an essential prerequisite for many successful
artificial intelligence and machine learning models. However, in real life applications these …
artificial intelligence and machine learning models. However, in real life applications these …