Zobrazeno 1 - 10
of 2 019
pro vyhledávání: '"Sam, F"'
Random walks are widely used for mining networks due to the computational efficiency of computing them. For instance, graph representation learning learns a d-dimensional embedding space, so that the nodes that tend to co-occur on random walks (a pro
Externí odkaz:
http://arxiv.org/abs/2405.14194
Crops are constantly challenged by different environmental conditions. Seed treatment by nanomaterials is a cost-effective and environmentally-friendly solution for environmental stress mitigation in crop plants. Here, 56 seed nanopriming treatments
Externí odkaz:
http://arxiv.org/abs/2304.03928
Autor:
Juliet W. Lefferts, Suzanne Kroes, Matthew B. Smith, Paul J. Niemöller, Natascha D. A. Nieuwenhuijze, Heleen N. Sonneveld van Kooten, Cornelis K. van der Ent, Jeffrey M. Beekman, Sam F. B. van Beuningen
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-9 (2024)
Abstract Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly being used for preclinical studies, drug development and precision medicine applications. Epithelial fluid transport properties in PDOs can be me
Externí odkaz:
https://doaj.org/article/57f8cce43d4e4914a932dc910bdf96e7
Autor:
Sweere, Sam F., Valtchanov, Ivan, Lieu, Maggie, Vojtekova, Antonia, Verdugo, Eva, Santos-Lleo, Maria, Pacaud, Florian, Briassouli, Alexia, Pérez, Daniel Cámpora
The field of artificial intelligence based image enhancement has been rapidly evolving over the last few years and is able to produce impressive results on non-astronomical images. In this work we present the first application of Machine Learning bas
Externí odkaz:
http://arxiv.org/abs/2205.01152
Autor:
Kansaana, C., Sam, F., Faanu, A., Glover, E.T., Akrobortu, E., Adofo, E.A., Annan, R.A.T., Essel, P., Adeti, P.J., Owusu, Isaac
Publikováno v:
In Radiation Physics and Chemistry January 2025 226
Probabilistic neural networks for predicting energy dissipation rates in geophysical turbulent flows
Motivated by oceanographic observational datasets, we propose a probabilistic neural network (PNN) model for calculating turbulent energy dissipation rates from vertical columns of velocity and density gradients in density stratified turbulent flows.
Externí odkaz:
http://arxiv.org/abs/2112.01113
Autor:
Peach, Robert L., Greenbury, Sam F., Johnston, Iain G., Yaliraki, Sophia N., Lefevre, David, Barahona, Mauricio
The intrinsic temporality of learning demands the adoption of methodologies capable of exploiting time-series information. In this study we leverage the sequence data framework and show how data-driven analysis of temporal sequences of task completio
Externí odkaz:
http://arxiv.org/abs/2007.07003