Results 221 to 230 of about 395,732 (262)
Some of the next articles are maybe not open access.
Annual Review of Neuroscience, 2005
Neural network modeling is often concerned with stimulus-driven responses, but most of the activity in the brain is internally generated. Here, we review network models of internally generated activity, focusing on three types of network dynamics: (a) sustained responses to transient stimuli, which provide a model of working memory; (b) oscillatory ...
Tim P, Vogels +2 more
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Neural network modeling is often concerned with stimulus-driven responses, but most of the activity in the brain is internally generated. Here, we review network models of internally generated activity, focusing on three types of network dynamics: (a) sustained responses to transient stimuli, which provide a model of working memory; (b) oscillatory ...
Tim P, Vogels +2 more
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1989
Abstract : The primary objective of this project has been the development of systems that reason in dynamic and open-ended environment and that use networks as their primary representation language. The focus of our research has been temporal reasoning, neural networks, truth maintenance, and default reasoning.
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Abstract : The primary objective of this project has been the development of systems that reason in dynamic and open-ended environment and that use networks as their primary representation language. The focus of our research has been temporal reasoning, neural networks, truth maintenance, and default reasoning.
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Networks, Dynamics, and Modularity
Physical Review Letters, 2004The identification of general principles relating structure to dynamics has been a major goal in the study of complex networks. We propose that the special case of linear network dynamics provides a natural framework within which a number of interesting yet tractable problems can be defined.
Evan A, Variano +2 more
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Dynamic topology representing networks
Neural Networks, 2000In the present paper, we propose a new algorithm, namely the Dynamic Topology Representing Networks (DTRN) for learning both topology and clustering information from input data. In contrast to other models with adaptive architecture of this kind, the DTRN algorithm adaptively grows the number of output nodes by applying a vigilance test. The clustering
J, Si, S, Lin, M A, Vuong
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2011
This article explores dynamic networks and diffusion, with particular emphasis on evolving traces of enacted social relations. It begins with a review of models for the evolution of networks over time — making a distinction between ‘node-based’ and ‘edge-based’ models — and more specifically how and why networks change.
Peter Dodds, Duncan J. Watts
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This article explores dynamic networks and diffusion, with particular emphasis on evolving traces of enacted social relations. It begins with a review of models for the evolution of networks over time — making a distinction between ‘node-based’ and ‘edge-based’ models — and more specifically how and why networks change.
Peter Dodds, Duncan J. Watts
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A cursory look at the empirical and even the theoretical organizational network literature presents a rather unbalanced picture in terms of the focus of the current research. Specifically, while an extensive body of knowledge exists on network outcomes and on how network structures may contribute to the creation of outcomes at different levels of ...
Gautam Auhja +2 more
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Gautam Auhja +2 more
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
exaly
2019
A language of nodes and links, degree and moments, and adjacency matrix and distance matrix, among others, is defined and used to capture the wide range of different types and properties of network topologies. Regular graphs and random graphs have fundamentally different connectivities that play a role in dynamic processes such as diffusion and ...
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A language of nodes and links, degree and moments, and adjacency matrix and distance matrix, among others, is defined and used to capture the wide range of different types and properties of network topologies. Regular graphs and random graphs have fundamentally different connectivities that play a role in dynamic processes such as diffusion and ...
openaire +1 more source