Preface: Characterisation of Physical Processes from Anomalous Diffusion Data
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Abstract (arXiv)
Preface to the special issue "Characterisation of Physical Processes from Anomalous Diffusion Data" associated with the Anomalous Diffusion Challenge ( https://andi-challenge.org ) and published in Journal of Physics A: Mathematical and Theoretical. The list of articles included in the special issue can be accessed at https://iopscience.iop.org/journal/1751-8121/page/Characterisation-of-Physical-Processes-from-Anomalous-Diffusion-Data .
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 8 of its 41 references that are in the map. First posted on arXiv 2 Jan 2023.
Builds on
8 of 41 references.
References · 8
- 2021Learning physical properties of anomalous random walks using graph neural networkscited by 10
- 2019Machine learning method for single trajectory characterizationcited by 8
- 2021Efficient recurrent neural network methods for anomalously diffusing single particle short and noisy trajectoriescited by 8
- 2021Unsupervised learning of anomalous diffusion datacited by 8
- 2021WaveNet-Based Deep Neural Networks for the Characterization of Anomalous Diffusion (WADNet)cited by 7
- 2021Bayesian inference of scaled versus fractional Brownian motioncited by 6
- 2022Characterization of anomalous diffusion through convolutional transformerscited by 6
- 2021Extreme Learning Machine for the Characterization of Anomalous Diffusion from Single Trajectories (AnDi-ELM)cited by 5
Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 1.
3 papers.
- 2024Machine Learning Analysis of Anomalous Diffusioncited by 3
- 2023Machine-Learning Solutions for the Analysis of Single-Particle Diffusion Trajectoriescited by 2
- 2025Data-Efficient Learning of Anomalous Diffusion with Wavelet Representations: Enabling Direct Learning from Experimental Trajectoriescited by 0
- 2025Data-Efficient Learning of Anomalous Diffusion with Wavelet Representations: Enabling Direct Learning from Experimental Trajectories9 Dec 2025
- 2024Machine Learning Analysis of Anomalous Diffusion2 Dec 2024
- 2023Machine-Learning Solutions for the Analysis of Single-Particle Diffusion Trajectories18 Aug 2023