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Bayesian deep learning for error estimation in the analysis of anomalous diffusion
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed sy...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640593/ https://www.ncbi.nlm.nih.gov/pubmed/36344559 http://dx.doi.org/10.1038/s41467-022-34305-6 |