Results 31 to 40 of about 212,177 (318)
Deep generative model for probabilistic wind speed and wind power estimation at a wind farm
Energy Science & Engineering, 2022 This work introduces a novel method to generate probabilistic hub‐height wind speed forecasts aimed at power output prediction. We employ state‐of‐the‐art convolutional variational autoencoders (CVAEs) trained with historical wind speed observations ...
Andrés A. Salazar +3 more
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Future of the Artificial Intelligence: Object of Law or Legal Personality?
Journal of Digital Technologies and Law, 2023 Objective: to reveal the problems associated with legal regulation of public relations, in which artificial intelligence systems are used, and to rationally comprehend the possibility of endowing such systems with a legal subject status, which is being ...
I. A. Filipova, V. D. Koroteev
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Deep Generative Models Enable Navigation in Sparsely Populated Chemical Space [PDF]
, 2021 Deep generative models are powerful tools for the exploration of chemical space, enabling the on-demand gener- ation of molecules with desired physical, chemical, or biological properties.
R. Greg, Stacey +3 more
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Graphical representation of internal model and generative model of behaviour. [PDF]
, 2022 Left: Internal model, generative model of the sequence assumed by the participant. Right: generative model of behaviour. (TIF)
Dezső Németh (11264079) +5 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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Relationally reflexive practice : a generative approach to theory development in qualitative research [PDF]
, 2014 In this article we explain how the development of new organization theory faces several mutually reinforcing problems, which collectively suppress generative debate and the creation of new and alternative theories.
Sillince, John +6 more
core +1 more source
Modelling control in generation [PDF]
Proceedings of the Eleventh European Workshop on Natural Language Generation - ENLG '07, 2007 In this paper we present a view of natural language generation in which the control structure of the generator is clearly separated from the content decisions made during generation, allowing us to explore and compare different control strategies in a systematic way.
Roger Evans +4 more
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Generative Marginalization Models
CoRR, 2023 We introduce marginalization models (MAMs), a new family of generative models for high-dimensional discrete data. They offer scalable and flexible generative modeling by explicitly modeling all induced marginal distributions. Marginalization models enable fast approximation of arbitrary marginal probabilities with a single forward pass of the neural ...
Sulin Liu +2 more
openaire +3 more sources
Modern-Day Shakespeare: Training Set Experiments with a Generative Pre-Trained Transformer - Best Paper [PDF]
, 2021 Best of Showcase PaperThe project's goal is to explore the field of natural language processing, particularly the use of a generative pre-trained transformer (GPT) to produce poetry.
Sheverack, Roksolana
core
Journal of Advances in Modeling Earth Systems, 2023 Subgrid parameterizations of mesoscale eddies continue to be in demand for climate simulations. These subgrid parameterizations can be powerfully designed using physics and/or data‐driven methods, with uncertainty quantification.
Pavel Perezhogin +2 more
doaj +1 more source