networks. The study of robustness in complex networks is important for many fields. In ecology, robustness is an important attribute of ecosystems, and can...

(graph theory) – Basic concept of graph theory Robustness of complex networks – Ability of a complex network to withstand failures and perturbations Michael...

context of network theory, a complex network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such...

computer science, robustness is the ability of a computer system to cope with errors during execution and cope with erroneous input. Robustness can encompass...

important observation related to the robustness of complex networks. According to this finding the critical points of the system are not necessarily the...

Robustness of complex networks – Ability of a complex network to withstand failures and perturbations Efficiency (network science) – measure of how efficiently...

interactions within complex bipartite networks may be nested as well. More specifically, bipartite ecological and organisational networks of mutually beneficial...

Applications of network theory include logistical networks, the World Wide Web, Internet, gene regulatory networks, metabolic networks, social networks, epistemological...

In evolutionary biology, robustness of a biological system (also called biological or genetic robustness) is the persistence of a certain characteristic...

social networks, wikis such as Wikipedia, gene networks, and even the underlying architecture of the Internet. It is the inspiration for many network-on-chip...

connectivity of nodes decide the topology of networks, which has an effect on robustness of network, the attribute discussed above. If the number of links between...

inspired by the structure and functions of biological neural networks. A neural network consists of connected units or nodes called artificial neurons, which...

developed techniques using graph curvature ideas for analyzing the robustness of complex networks, with many applications to cancer genomic analysis. He gave...

forms of robustness in protein interaction networks. Those authors suggest that similar phenomena is likely to arise in other biological networks and potentially...

social networks, as well as "digital traces" regarding face-to-face networks. In general, social networks are self-organizing, emergent, and complex, such...

Physics-informed neural networks (PINNs), also referred to as Theory-Trained Neural Networks (TTNs), are a type of universal function approximators that...

study of complex systems. Barabási's work challenged the prevailing notion that complex networks could be adequately modeled as random networks. He is...

relevant metric to quantitatively characterize real complex networks and can also be used to quantify network complexity According to a 2018 publication by...

Deneubourg, J.L.; Theraulaz, G. (November 2002). "Efficiency and robustness in ant networks of galleries". The European Physical Journal B. 42 (1): 123–129...

information theory on complex networks when a competitive cluster growth process is applied to the network. In models of scale-free ideal networks it is possible...

small-world networks self-stabilization and scale-free networks. These emerge from bottom-up interactions, unlike top-down hierarchical networks within organizations...

topology of the overlay network may (and often does) differ from that of the underlying one. For example, many peer-to-peer networks are overlay networks. They...

limitation by integrating RL and deep neural networks. This combination enables agents to approximate complex functions and handle unstructured input data...

behavior that changes over time. Social networks Diffusion of technologies and information Cooperation Social norms Complex adaptive system Complexity science...

Graph neural networks (GNN) are specialized artificial neural networks that are designed for tasks whose inputs are graphs. One prominent example is molecular...

down into its parts. It has been used as a way of exploring and developing effective action in complex contexts, enabling systems change. Systems thinking...

collection of addresses in the network is called the address space of the network. Examples of telecommunications networks include computer networks, the Internet...

friend-to-friend networks, as well as large, popular networks such as Tor, Hyphanet, I2P, and Riffle operated by public organizations and individuals. Users of the...

propagation, decisions, and robustness of large dynamic networks arising in transportation, energy, finance, and social networks. On the applied side, Dahleh...

Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive...