94 citations · 154 across the 4 of their papers we have counts for
4 papers
Change-point detection in anomalous-diffusion trajectories utilising machine-learning-based uncertainty estimates
Henrik Seckler, Ralf Metzler
When recording the movement of individual animals, cells or molecules one will often observe changes in their diffusive behaviour at certain points in time along their trajectory.…
Multifractal-spectral features enhance classification of anomalous diffusion
Henrik Seckler, Ralf Metzler, Damian G. Kelty-Stephen +1
Anomalous diffusion processes pose a unique challenge in classification and characterization. Previously (Mangalam et al., 2023, Physical Review Research 5, 023144), we established…
Machine-Learning Solutions for the Analysis of Single-Particle Diffusion Trajectories
Henrik Seckler, Janusz Szwabinski, Ralf Metzler
Single-particle traces of the diffusive motion of molecules, cells, or animals are by-now routinely measured, similar to stochastic records of stock prices or weather data. Deciphe…
Bayesian deep learning for error estimation in the analysis of anomalous diffusion
Henrik Seckler, Ralf Metzler
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 e…