Search Results for author:
Found 3 papers, 2 papers with code
Variational inference of fractional Brownian motion with linear computational complexity
Our approach learns the posterior distribution of the walks' parameters with a likelihood-free method.
Learning physical properties of anomalous random walks using graph neural networks
Here, we introduce a new, fast approach to inferring random walk properties based on graph neural networks (GNNs).
Statistical Tests for Force Inference in Heterogeneous Environments
We devise a method to detect and estimate forces in a heterogeneous environment based on experimentally recorded stochastic trajectories.
Biological Physics Chemical Physics Biomolecules Quantitative Methods
