Results 301 to 310 of about 24,500,069 (341)
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2019
Neuroscience studies inspire that structures are needed in the hidden space of deep learning models. In this paper, we propose a capsule restricted Boltzmann machine and a capsule Helmholtz machine by replacing individual hidden variables with encapsulated groups of hidden variables.
Li, Yifeng, Zhu, Xiaodan
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Neuroscience studies inspire that structures are needed in the hidden space of deep learning models. In this paper, we propose a capsule restricted Boltzmann machine and a capsule Helmholtz machine by replacing individual hidden variables with encapsulated groups of hidden variables.
Li, Yifeng, Zhu, Xiaodan
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Current Opinion in Psychology, 2018
The General Aggression Model (GAM) is a comprehensive, integrative, framework for understanding aggression. It considers the role of social, cognitive, personality, developmental, and biological factors on aggression. Proximate processes of GAM detail how person and situation factors influence cognitions, feelings, and arousal, which in turn affect ...
Johnie J, Allen +2 more
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The General Aggression Model (GAM) is a comprehensive, integrative, framework for understanding aggression. It considers the role of social, cognitive, personality, developmental, and biological factors on aggression. Proximate processes of GAM detail how person and situation factors influence cognitions, feelings, and arousal, which in turn affect ...
Johnie J, Allen +2 more
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Overlapping Generations Model of General Equilibrium [PDF]
, 1987 The consumption loan model that Paul Samuelson introduced in 1958 to analyse the rate of interest, with or without the social contrivance of money, has developed into what is without doubt the most important and influential paradigm in neoclassical general equilibrium theory outside of the Arrow—Debreu economy.
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Trans. Mach. Learn. Res.
Modularization is a cornerstone of computer science, abstracting complex functions into atomic building blocks. In this paper, we introduce a new level of modularization by abstracting generative models into atomic generative modules.
Tianhong Li +3 more
semanticscholar +1 more source
Modularization is a cornerstone of computer science, abstracting complex functions into atomic building blocks. In this paper, we introduce a new level of modularization by abstracting generative models into atomic generative modules.
Tianhong Li +3 more
semanticscholar +1 more source
Generalized plaid models [PDF]
Neurocomputing, 2012 The problem of two-way clustering has attracted considerable attention in diverse research areas such as functional genomics, text mining, and market research, where people want to simultaneously cluster rows and columns of a data matrix. In this paper, we propose a family of generalized plaid models for two-way clustering, where the layer estimation ...
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Companion of the 18th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications - OOPSLA '03, 2003
The Generative Model Transformer (GMT) project is an Open Source initiative to build a Model Driven Architecure™ tool that allows fully customisable Platform Independent Models, Platform Description Models, Texture Mappings, and Refinement Transformations.
Jorn Bettin, Ghica van Emde Boas
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The Generative Model Transformer (GMT) project is an Open Source initiative to build a Model Driven Architecure™ tool that allows fully customisable Platform Independent Models, Platform Description Models, Texture Mappings, and Refinement Transformations.
Jorn Bettin, Ghica van Emde Boas
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GenAI Arena: An Open Evaluation Platform for Generative Models
Neural Information Processing SystemsGenerative AI has made remarkable strides to revolutionize fields such as image and video generation. These advancements are driven by innovative algorithms, architecture, and data.
Dongfu Jiang +6 more
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VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models
European Conference on Computer VisionThis paper presents a novel method for building scalable 3D generative models utilizing pre-trained video diffusion models. The primary obstacle in developing foundation 3D generative models is the limited availability of 3D data.
Junlin Han +2 more
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1988
The new relation between programming and modelling is discussed. Some important developments on the field of modelling and simulation support systems and their connection with AI are pointed out. Modelling of generic objects and processes is an efficient tool for complexity reduction of models.
V. Wenzel, E. Matthaus, M. Flechsig
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The new relation between programming and modelling is discussed. Some important developments on the field of modelling and simulation support systems and their connection with AI are pointed out. Modelling of generic objects and processes is an efficient tool for complexity reduction of models.
V. Wenzel, E. Matthaus, M. Flechsig
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Machine Unlearning for Image-to-Image Generative Models
International Conference on Learning RepresentationsMachine unlearning has emerged as a new paradigm to deliberately forget data samples from a given model in order to adhere to stringent regulations.
Guihong Li +3 more
semanticscholar +1 more source