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Henrik Seckler

Showing results (1-10 of 4) with videos related to

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Nature Communications|November 7, 2022
Bayesian deep learning for error estimation in the analysis of anomalous diffusionHenrik Seckler, Ralf Metzler
Nature Communications|November 30, 2023
Author Correction: Bayesian deep learning for error estimation in the analysis of anomalous diffusionHenrik Seckler, Ralf Metzler
The Journal of Physical Chemistry Letters|August 30, 2023
Machine-Learning Solutions for the Analysis of Single-Particle Diffusion TrajectoriesHenrik Seckler, Janusz Szwabiński, Ralf Metzler
Physical Review. E|May 17, 2024
Multifractal spectral features enhance classification of anomalous diffusionHenrik Seckler, Ralf Metzler, Damian G Kelty-Stephen, et al.
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Showing results (1-10 of 4) with videos related to

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Pageof 1
Nature Communications|November 7, 2022
Bayesian deep learning for error estimation in the analysis of anomalous diffusionHenrik Seckler, Ralf Metzler
Nature Communications|November 30, 2023
Author Correction: Bayesian deep learning for error estimation in the analysis of anomalous diffusionHenrik Seckler, Ralf Metzler
The Journal of Physical Chemistry Letters|August 30, 2023
Machine-Learning Solutions for the Analysis of Single-Particle Diffusion TrajectoriesHenrik Seckler, Janusz Szwabiński, Ralf Metzler
Physical Review. E|May 17, 2024
Multifractal spectral features enhance classification of anomalous diffusionHenrik Seckler, Ralf Metzler, Damian G Kelty-Stephen, et al.
Pageof 1