anomalous-diffusion

Stochastic processes insights from VAE. Code for the paper: Learning minimal representations of stochastic processes with variational autoencoders.

KISTEP modular pipeline for the characterization of anomalous diffusion trajectories.

This repository contains Python (Jupyter Notebooks), C and Shell code, which was used to generate figures in a paper under the same name.

Codes and instructions to replicate the research published in Cobarrubia et al. Frontiers in Physics 2021.

Regime diagnostics for spatiotemporal kernels K(r,t), 1D-4D: transport × coherence classification, isotropic S(k,ω) via Hankel/spherical-Bessel, plus stateflow — a domain-agnostic trajectory layer. NumPy/SciPy only. pip install kernel-dynamics-viewer

Exploration of voter model with power law time-dependent event rates

First explicit curvature correction formula for fractional Laplacians on curved manifolds. Complete proof via heat kernel expansion, validated computationally on S². Applications in anomalous diffusion, thermal field theory, and curved spacetime physics.

This repository contains the code for the analysis reported in Physical Review E 96, 022417.

Dynamic Weighted Fractional Entropy for Time-Fractional Diffusion Processes via Moment Formulas

3D Slicer extension that provides several approaches in order to apply the anomalous spatial filters on medical images.