Results 41 to 50 of about 65,539 (306)
Model Reduction Through Progressive Latent Space Pruning in Deep Active Inference
Frontiers in Neurorobotics, 2022 Although still not fully understood, sleep is known to play an important role in learning and in pruning synaptic connections. From the active inference perspective, this can be cast as learning parameters of a generative model and Bayesian model ...
Samuel T. Wauthier +4 more
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Multimodal Sensor Fusion Using Symmetric Skip Autoencoder Via an Adversarial Regulariser
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 The fusion of the spatial characteristics, of visual image, and spectral aspects, of infrared image, is of immense practical importance. In this work, we propose a novel spatially constrained adversarial autoencoder that extracts deep features from the ...
Snigdha Bhagat +3 more
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Modeling Procedural Knowledge: A Generative Modeler for Cultural Heritage
, 2010 Within the last few years generative modeling techniques have gained attention especially in the context of cultural heritage. As a generative model describes a rather ideal object than a real one, generative techniques are a basis for object description
Martin Strobl +7 more
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ProT-GFDM: A generative fractional diffusion model for protein generation
Computational and Structural Biotechnology JournalThis work introduces the generative fractional diffusion model for protein generation (ProT-GFDM), a novel generative framework that employs fractional stochastic dynamics for protein backbone structure modeling.
Xiao Liang +4 more
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NatureAbstract Generative models cover various application areas, including image and video synthesis, natural language processing and molecular design, among many others1–11. As digital generative models become larger, scalable inference in a fast and energy-efficient manner becomes a challenge12–14.
Shiqi Chen +4 more
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A generative model for music transcription
, 2006 In this paper, we present a graphical model for polyphonic music transcription. Our model, formulated as a dynamical Bayesian network, embodies a transparent and computationally tractable approach to this acoustic analysis problem.
Barber, D. +5 more
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Digital EngineeringHealthcare economic evaluation increasingly relies on predictive modeling to inform resource allocation decisions. Traditional cost-effectiveness analysis (CEA) methodologies face significant challenges when processing complex, heterogeneous healthcare ...
Aanuoluwapo Clement David-Olawade +4 more
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Automatic model generation [PDF]
Proceedings of the 18th conference on Winter simulation - WSC '86, 1986 The Facility Analysis and Simulation Technique (FAST) is a product which has been developed by the Electronics Automation Application Center (EAAC) of the General Electric Company. Currently in version 2.0, FAST has been developed to analyze electronics facilities resource requirements by utilizing years of EAAC expertise in this environment.
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ezRealtime: A Domain-Specific Modeling Tool for Embedded Hard Real-Time Software Synthesis
, 2008 In this paper, we introduce the ezRealtime project, which relies on the Time Petri Net (TPN) formalism and defines a Domain-Specific Modeling (DSM) tool to provide an easy- to-use environment for specifying Embedded Hard Real-Time (EHRT) systems and for ...
Fabiano Cruz +8 more
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On Generalizations of the Engset Model [PDF]
IEEE Communications Letters, 2007 The Engset model has been extensively studied and widely used for blocking probability evaluation in telecommunications networks. In 1957, J.W. Cohen considered two generalizations of the Engset model: 1) permitting the distributions of the holding time and interarrival time to differ from source to source; 2) permitting the idle time distribution to ...
Eric W. M. Wong +2 more
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