Results 241 to 250 of about 549,366 (277)
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Behavioral and Brain Sciences, 2017
AbstractWe argue that general intelligence, as presented in the target article, generates multiple distinct and non-equivalent characterisations. Clarifying this central concept is necessary for assessing Burkart et al.'s proposal that the cultural intelligence hypothesis is the best explanation for the evolution of general intelligence. We assess this
Andrew, Buskell, Marta, Halina
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AbstractWe argue that general intelligence, as presented in the target article, generates multiple distinct and non-equivalent characterisations. Clarifying this central concept is necessary for assessing Burkart et al.'s proposal that the cultural intelligence hypothesis is the best explanation for the evolution of general intelligence. We assess this
Andrew, Buskell, Marta, Halina
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Generative Inference Network for Imbalanced Domain Generalization
IEEE Transactions on Image Processing, 2023Domain generalization (DG) aims to learn transferable knowledge from multiple source domains and generalize it to the unseen target domain. To achieve such expectation, the intuitive solution is to seek domain-invariant representations via generative adversarial mechanism or minimization of cross-domain discrepancy.
Haifeng Xia, Taotao Jing, Zhengming Ding
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General-relativistic domain walls
Physical Review D, 1989Domain walls naturally arise in any model that has a spontaneously broken discrete symmetry. In the simplest example, symmetry breaking is accomplished by a real scalar field. We investigate infinite domain walls in general relativity using the full Einstein scalar-field equations.
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2002
The following three sections provide a description of the generic classification system used in this study. The agreement between the domain information and the observation data, both represented by fuzzy sets, is determined by an assessment of the compatibility of the two fuzzy sets.
Valerie V. Cross, Thomas A. Sudkamp
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The following three sections provide a description of the generic classification system used in this study. The agreement between the domain information and the observation data, both represented by fuzzy sets, is determined by an assessment of the compatibility of the two fuzzy sets.
Valerie V. Cross, Thomas A. Sudkamp
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2018
Conventional domain adaptation assumes that target data are still accessible in the training stage. However, we would always confront such cases in reality that the target data are totally blind in the training stage. This is extremely challenging since we have no prior knowledge of the target.
Zhengming Ding, Handong Zhao, Yun Fu
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Conventional domain adaptation assumes that target data are still accessible in the training stage. However, we would always confront such cases in reality that the target data are totally blind in the training stage. This is extremely challenging since we have no prior knowledge of the target.
Zhengming Ding, Handong Zhao, Yun Fu
openaire +1 more source