Results 51 to 60 of about 1,260,387 (211)
Cosmic shear covariance: The log-normal approximation [PDF]
, 2011 [Abridged] We seek approximations to the cosmic shear covariance that are as easy to use as the common approximations based on normal statistics, but yield more accurate covariance matrices and parameter errors. We derive expressions for the cosmic shear covariance under the assumption that the underlying convergence field follows log-normal statistics.
arxiv +1 more source
Extended Batch Normalization [PDF]
arXiv, 2020 Batch normalization (BN) has become a standard technique for training the modern deep networks. However, its effectiveness diminishes when the batch size becomes smaller, since the batch statistics estimation becomes inaccurate. That hinders batch normalization's usage for 1) training larger model which requires small batches constrained by memory ...
arxiv
Foucault for Heisman: College Football and the Liturgies of Power
Religions, 2020 This essay attempts to give a new sort of answer to the question of whether or not sport and sports fandom are a religion through the work of Foucault on “power.” Looking specifically at college football in North America, I examine the ways ...
Jason M. Smith
doaj +1 more source
AFN: Adaptive Fusion Normalization via an Encoder-Decoder Framework [PDF]
arXiv, 2023 The success of deep learning is inseparable from normalization layers. Researchers have proposed various normalization functions, and each of them has both advantages and disadvantages. In response, efforts have been made to design a unified normalization function that combines all normalization procedures and mitigates their weaknesses.
arxiv
Siglec-15 as an immune suppressor and potential target for normalization cancer immunotherapy
Nature Network Boston, 2019 Overexpression of the B7-H1 (PD-L1) molecule in the tumor microenvironment (TME) is a major immune evasion mechanism in some patients with cancer, and antibody blockade of the B7-H1/PD-1 interaction can normalize compromised immunity without excessive ...
Jun Wang +18 more
semanticscholar +1 more source
Ordered quantile normalization: a semiparametric transformation built for the cross-validation era
Journal of Applied Statistics, 2019 Normalization transformations have recently experienced a resurgence in popularity in the era of machine learning, particularly in data preprocessing. However, the classical methods that can be adapted to cross-validation are not always effective.
Ryan A. Peterson, J. Cavanaugh
semanticscholar +1 more source
Veterinary Medicine and Science, 2021 Stress factors during poultry production can evoke changes in gene transcription and protein synthesis in the hen oviduct and could affect the internal and external egg quality.
Roy Rodríguez‐Hernández +2 more
doaj +1 more source
Learning Graph Normalization for Graph Neural Networks [PDF]
arXiv, 2020 Graph Neural Networks (GNNs) have attracted considerable attention and have emerged as a new promising paradigm to process graph-structured data. GNNs are usually stacked to multiple layers and the node representations in each layer are computed through propagating and aggregating the neighboring node features with respect to the graph.
arxiv
Normalization: A Preprocessing Stage [PDF]
arXiv, 2015 As we know that the normalization is a pre-processing stage of any type problem statement. Especially normalization takes important role in the field of soft computing, cloud computing etc. for manipulation of data like scale down or scale up the range of data before it becomes used for further stage.
arxiv
O paradigma e a vivência: a busca da identidade
Filologia e Linguística Portuguesa, 1997 By outlying grammar along the classical lines transmitted by the medieval Latin tradition, Portuguese grammarians, as well as Castillian, French and Italian peers, are simultaneously building a new paradigm: the Romance consciousness. This consciousness,
Maria Leonor Carvalhão Buescu
doaj +1 more source