Sequence-to-sequence change-point detection in single-particle trajectories via recurrent neural network for measuring self-diffusion

HIGHLIGHTS

• who: Q. Martinez from the Department of Mechanical and Aerospace Engineering, Brunel University London, Uxbridge , PH, UK have published the Article: Sequence-to-Sequence Change-Point Detection in Single-Particle Trajectories via Recurrent Neural Network for Measuring Self-Diffusion, in the Journal: (JOURNAL)
• what: Through several artificial and simulated scenarios the authors demonstrate the compelling accuracy of the model for dissecting linear and nonlinear behaviour. The authors show that the transition density function has fundamental implications and correspondence to underlying mechanisms that influence transition. The authors show that the known proportionality between salt concentration and . . .
  

   

  

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