Results 11 to 20 of about 42,084 (260)
Bayesian Spillover Graphs for Dynamic Networks
CoRR, 2022 We present Bayesian Spillover Graphs (BSG), a novel method for learning temporal relationships, identifying critical nodes, and quantifying uncertainty for multi-horizon spillover effects in a dynamic system. BSG leverages both an interpretable framework via forecast error variance decompositions (FEVD) and comprehensive uncertainty quantification via ...
Grace Deng, David S. Matteson
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Dynamic Bayesian networks for meeting structuring [PDF]
2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004 The paper is about the automatic structuring of multiparty meetings using audio information. We have used a corpus of 53 meetings, recorded using a microphone array and lapel microphones for each participant. The task was to segment meetings into a sequence of meeting actions, or phases.
Alfred Dielmann, Steve Renals
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Bayesian Nonparametrics for Sparse Dynamic Networks
, 2023 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]
Jisuanji kexue, 2022 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
Journal of Artificial Intelligence Research, 2005 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
Xibei Gongye Daxue Xuebao, 2020 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
IEEE Access, 2019 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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Grid Quality of Service Trustworthiness Evaluation Based on Bayesian Network
IEEE Access, 2020 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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Asynchronous Dynamic Bayesian Networks
CoRR, 2012 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
CoRR, 2022 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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