Results 61 to 70 of about 219,196 (280)
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Nurses are central to cancer care for children and adolescents, yet no comprehensive synthesis has defined essential core competencies for pediatric oncology nursing (PON) practice internationally, particularly in Latin America and the Caribbean (LAC).
Luís Carlos Lopes‐Júnior +7 more
wiley +1 more source
Some inequalities for Csiszár divergence via theory of time scales
Advances in Difference Equations, 2020 In this paper, we present some inequalities for Csiszár f-divergence between two probability measures on time scale. These results extend some known results in the literature and offer new results in h-discrete calculus and quantum calculus.
Iqrar Ansari +4 more
doaj +1 more source
Variational f-divergence Minimization
, 2019 Probabilistic models are often trained by maximum likelihood, which corresponds to minimizing a specific f-divergence between the model and data distribution. In light of recent successes in training Generative Adversarial Networks, alternative non-likelihood training criteria have been proposed.
Zhang, Mingtian +4 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Pulmonary dysfunction and sleep abnormalities are common in children with sickle cell disease (SCD) and are associated with worse clinical outcomes. Whether spirometry abnormalities are associated with polysomnography (PSG) findings remains unclear.
Ammar Saadoon Alishlash +4 more
wiley +1 more source
New information inequalities with two measures using new F-divergence and convex function
Partial Differential Equations in Applied MathematicsThe applications of divergence measures in the fields of information is the study of related problems in information processing, information storage, information retrieval and so on.
Anulika Sharma +4 more
doaj +1 more source
Stabilizing Training of Generative Adversarial Networks through Regularization
, 2017 Deep generative models based on Generative Adversarial Networks (GANs) have demonstrated impressive sample quality but in order to work they require a careful choice of architecture, parameter initialization, and selection of hyper-parameters.
Hofmann, Thomas +3 more
core +1 more source
Monotonicity of optimized quantum f-divergence [PDF]
Quantum Information ProcessingAbstractOptimized quantumf-divergence was first introduced by Wilde and further explored by Li and Wilde later. Wilde raised the question of whether the monotonicity of optimized quantumf-divergence can be generalized to maps that are not quantum channels.
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The management of clinically apparent single lesions or oligofocal nephroblastomatosis, a facultative precursor of nephroblastoma, remains debated. Methods We retrospectively analyzed 37 patients with clinically apparent single or oligofocal nephroblastomatosis (two to three lesions per kidney) among 2347 patients registered between
Nils Welter +17 more
wiley +1 more source
Correlations of Cross-Entropy Loss in Machine Learning
EntropyCross-entropy loss is crucial in training many deep neural networks. In this context, we show a number of novel and strong correlations among various related divergence functions.
Richard Connor +3 more
doaj +1 more source
Genome Biology, 2019 Background Genomic variation is widespread, and both neutral and selective processes can generate similar patterns in the genome. These processes are not mutually exclusive, so it is difficult to infer the evolutionary mechanisms that govern population ...
Baosheng Wang +11 more
doaj +1 more source