scispace - formally typeset
H

Hippolyte Verdier

Researcher at University of Paris

Publications -  14
Citations -  151

Hippolyte Verdier is an academic researcher from University of Paris. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 3, co-authored 4 publications receiving 17 citations. Previous affiliations of Hippolyte Verdier include Union Pacific Railroad.

Papers
More filters
Journal ArticleDOI

Objective comparison of methods to decode anomalous diffusion.

TL;DR: The Anomalous Diffusion Challenge (AnDi) as mentioned in this paper was an open competition for the characterization of anomalous diffusion from the measurement of an individual trajectory, which traditionally relies on calculating the trajectory mean squared displacement.
Posted Content

Objective comparison of methods to decode anomalous diffusion

TL;DR: This paper presents a meta-anatomy of the response of the immune system to chemotherapy, a model derived from the model developed by Carl Friedrich Gauss in 1916.
Journal ArticleDOI

Learning physical properties of anomalous random walks using graph neural networks

TL;DR: In this article, a graph neural network (GNN) is proposed to infer the physical properties of random walk models and their anomalous exponents by associating a vector of features with each position and a sparse graph structure with each observed trajectory.
Journal ArticleDOI

Learning physical properties of anomalous random walks using graph neural networks

TL;DR: In this article, a graph neural network (GNN) is proposed to infer the physical properties of random walk models and their anomalous exponents by associating a vector of features with each position and a sparse graph structure with each observed trajectory.
Posted ContentDOI

A maximum mean discrepancy approach reveals subtle changes in α-synuclein dynamics

TL;DR: A new statistical testing scheme to detect changes in biomolecule dynamics within organelles without needing to identify a model of their motion is developed and applied to detect differences in the dynamics of α-synuclein, a presynaptic protein, in axons and boutons during synaptic stimulation.