Results 31 to 40 of about 439,127 (183)
Detection of Rapidly Spreading Hashtags via Social Networks
IEEE Access, 2020 Social network services (SNSs) such as Twitter and Facebook have emerged as a new medium for communication. They offer a unique mechanism of sharing information by allowing users to receive all messages posted by those whom they “follow” ...
Younghoon Kim, Jiwon Seo
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Any-Shot Learning From Multimodal Observations (ALMO)
IEEE Access, 2023 In this paper, we propose a framework (ALMO) for any-shot learning from multi-modal observations. Using training data containing both objects (inputs) and class attributes (side information) from multiple modalities, ALMO embeds the high-dimensional data
Mehmet Aktukmak +2 more
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Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo
, 2017 Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data.
Lindsten, Fredrik +3 more
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GPRGS: Sparse Input New View Synthesis Based on Probabilistic Modeling and Feature Regularization
Applied SciencesWhen the number of available training views is limited, the small quantity of images results in insufficient generation of Gaussian ellipsoids, leading to an empty Gaussian model.
Yinshuang Qin, Gen Liu, Jian Wang
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Journal of Marine Science and Engineering, 2020 Optimization of maintenance and design of coastal steel infrastructure needs for long-term predictive degradation models. The phenomenon of corrosion in the offshore and coastal environment is very complex due to the stochastic and changing nature of the
Franck Schoefs +2 more
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Modelling Probabilistic Wireless Networks [PDF]
Logical Methods in Computer Science, 2013 We propose a process calculus to model high level wireless systems, where the topology of a network is described by a digraph. The calculus enjoys features which are proper of wireless networks, namely broadcast communication and probabilistic behaviour.
Cerone, Andrea, Hennessy, Matthew
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InfrastructuresAccurate and reliable modeling of pavement deterioration is critical for effective infrastructure management. This study proposes a probabilistic machine learning framework using Bayesian-optimized Natural Gradient Boosting (BO-NGBoost) to predict the ...
Zhen Liu, Xingyu Gu, Wenxiu Wu
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Energies, 2020 Modern power system operation should comply with strictly reliability and security constraints, which aim at guarantee the correct system operation also in the presence of severe internal and external disturbances.
Ennio Brugnetti +4 more
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Probabilistic Programming Concepts [PDF]
, 2013 A multitude of different probabilistic programming languages exists today, all extending a traditional programming language with primitives to support modeling of complex, structured probability distributions.
De Raedt, Luc, Kimmig, Angelika
core
Denoising Diffusion Probabilistic Models for Probabilistic Energy Forecasting
2023 IEEE Belgrade PowerTech, 2023 Scenario-based probabilistic forecasts have become vital for decision-makers in handling intermittent renewable energies. This paper presents a recent promising deep learning generative approach called denoising diffusion probabilistic models. It is a class of latent variable models which have recently demonstrated impressive results in the computer ...
Capel, Esteban Hernandez +1 more
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