Structural Robustness of Complex Networks: A Survey of A Posteriori Measures [Feature]

Y Lou, L Wang, G Chen - IEEE Circuits and Systems Magazine, 2023 - ieeexplore.ieee.org
Network robustness is critical for various industrial and social networks against malicious
attacks, which has various meanings in different research contexts and here it refers to the …

A learning convolutional neural network approach for network robustness prediction

Y Lou, R Wu, J Li, L Wang, X Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Network robustness is critical for various societal and industrial networks against malicious
attacks. In particular, connectivity robustness and controllability robustness reflect how well a …

Classification-based prediction of network connectivity robustness

Y Lou, R Wu, J Li, L Wang, CB Tang, G Chen - Neural Networks, 2023 - Elsevier
Today, there is an increasing concern about malicious attacks on various networks in society
and industry, against which the network robustness is critical. Network connectivity …

Gaze tracking using an unmodified web camera and convolutional neural network

MF Ansari, P Kasprowski, M Obetkal - Applied Sciences, 2021 - mdpi.com
Gaze estimation plays a significant role in understating human behavior and in human–
computer interaction. Currently, there are many methods accessible for gaze estimation …

An adaptive attack model to network controllability

S Li, W Liu, R Wu, J Li - Reliability Engineering & System Safety, 2023 - Elsevier
For the ultimate goal of protecting the network controllability and enhancing the
controllability robustness, one can learn from how a network can be effectively destructed. In …

Comprehensive analysis of network robustness evaluation based on convolutional neural networks with spatial pyramid pooling

W Jiang, T Fan, C Li, C Zhang, T Zhang, Z Luo - Chaos, Solitons & Fractals, 2024 - Elsevier
Connectivity robustness, crucial for network understanding, optimization, and repair, has
been evaluated traditionally through time-consuming and often impractical simulations …

Scalable rapid framework for evaluating network worst robustness with machine learning

W Jiang, P Li, T Fan, T Li, C Zhang, T Zhang… - Reliability Engineering & …, 2024 - Elsevier
Robustness is pivotal for comprehending, designing, optimizing, and rehabilitating networks,
with simulation attacks being the prevailing evaluation method. Simulation attacks are often …

Enhancing Network Robustness with Structural Prior and Evolutionary Techniques

J Huang, R Wu, J Li - Information Sciences, 2024 - Elsevier
Robustness optimization in complex networks is a critical research area due to its
implications for the reliability and stability of various systems. However, existing algorithms …

Spp-cnn: An efficient framework for network robustness prediction

C Wu, Y Lou, L Wang, J Li, X Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This paper addresses the robustness of a network to sustain its connectivity and
controllability against malicious attacks. This kind of network robustness is typically …

Distributed network reconstruction based on binary compressed sensing via ADMM

Y Liu, K Huang, C Yang, Z Wang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
At present, network model is a general framework for the representation of complex system,
and its structure is the fundamental and prerequisite for control and other applications of …