Results 1 to 10 of about 7,371,142 (245)
Granger causality vs. dynamic Bayesian network inference: a comparative study [PDF]
Background In computational biology, one often faces the problem of deriving the causal relationship among different elements such as genes, proteins, metabolites, neurons and so on, based upon multi-dimensional temporal data.
Feng Jianfeng, Zou Cunlu
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Bayesian Nonparametrics for Sparse Dynamic Networks
In this paper we propose a Bayesian nonparametric approach to modelling sparse time-varying networks. A positive parameter is associated to each node of a network, which models the sociability of that node. Sociabilities are assumed to evolve over time, and are modelled via a dynamic point process model. The model is able to capture long term evolution
Cian Naik +4 more
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Dynamic Network Security Analysis Based on Bayesian Attack Graphs [PDF]
In order to overcome the difficulties that current attack graph model cannot reflect real-time network attack events,a method is proposed including a forward risk probability update algorithm and a forward-backward combined risk probability update ...
LI Jia-rui, LING Xiao-bo, LI Chen-xi, LI Zi-mu, YANG Jia-hai, ZHANG Lei, WU Cheng-nan
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Relational Dynamic Bayesian Networks
Stochastic processes that involve the creation of objects and relations over time are widespread, but relatively poorly studied. For example, accurate fault diagnosis in factory assembly processes requires inferring the probabilities of erroneous assembly operations, but doing this efficiently and accurately is difficult.
Pedro M. Domingos +2 more
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A Timeliness-Enhanced Traffic Identification Method in Airborne Network
High dynamic topology and limited bandwidth of the airborne network make it difficult to provide reliable information interaction services for diverse combat mission of aviation swarm operations.
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Research on Unmanned Underwater Vehicle Threat Assessment
The unmanned underwater vehicle (UUV) plays an ever increasing and important role in the modern marine environment. In particular, the tasks of underwater reconnaissance and surveillance, underwater mine hunting and anti-submarine warfare, all poses a ...
Hongfei Yao +4 more
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Asynchronous Dynamic Bayesian Networks
Systems such as sensor networks and teams of autonomous robots consist of multiple autonomous entities that interact with each other in a distributed, asynchronous manner. These entities need to keep track of the state of the system as it evolves.
Avi Pfeffer, Terry Tai
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Bayesian Inference of Stochastic Dynamical Networks
Network inference has been extensively studied in several fields, such as systems biology and social sciences. Learning network topology and internal dynamics is essential to understand mechanisms of complex systems. In particular, sparse topologies and stable dynamics are fundamental features of many real-world continuous-time (CT) networks.
Yasen Wang +2 more
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Grid Quality of Service Trustworthiness Evaluation Based on Bayesian Network
Quality of Service (QoS) is applied to evaluate the satisfaction level of users using a service and it is a measure and evaluation of the service level of service providers.
Yiling Huang
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A DBN-DEVS Extension for Modeling and Simulate Uncertain Systems
In this paper, our goal is to propose a new extension to the Discrete Event System (DEVS) formalism, which is based on Dynamic Bayesian Network (DBN), and this extension will be called DBN-DEVS, which allows to modeling and simulate the uncertain ...
Sid Ahmed Mokhtar Mostefaoui +2 more
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