Efficient recurrent neural network methods for anomalously diffusing single particle short and noisy trajectories

5 August 2021

Papers citing "Efficient recurrent neural network methods for anomalously diffusing single particle short and noisy trajectories"

6 / 6 papers shown

Title
Machine Learning Analysis of Anomalous Diffusion Wenjie Cai Yi Hu X. Qu Hui Zhao Gongyi Wang Jing Li Zihan Huang 112 1 0 02 Dec 2024
$Variational inference of fractional Brownian motion with linear computational complexity$ Variational inference of fractional Brownian motion with linear computational complexity Hippolyte Verdier Franccois Laurent Alhassan Cassé Christian L. Vestergaard Jean-Baptiste Masson 165 6 0 15 Mar 2022
Spectral content of a single non-Brownian trajectory D. Krapf Nils Lukat E. Marinari Ralf Metzler G. Oshanin C. Selhuber‐Unkel A. Squarcini Lorenz Stadler M. Weiss Xinran Xu 32 99 0 01 Feb 2019
Large deviations of time-averaged statistics for Gaussian processes Janusz Gajda A. Wyłomańska H. Kantz A. Chechkin G. Sikora 27 8 0 27 Nov 2018
Power spectral density of a single Brownian trajectory: What one can and cannot learn from it D. Krapf E. Marinari Ralf Metzler G. Oshanin Xinran Xu A. Squarcini 29 80 0 09 Jan 2018
A Critical Review of Recurrent Neural Networks for Sequence Learning Zachary Chase Lipton John Berkowitz Charles Elkan 91 2,345 0 29 May 2015