Poster
in
Workshop: Machine Learning for Genomics Explorations (MLGenX)
To trap or not to trap--analyzing the trade-offs in diffusion transport models
Rushmila Shehreen Khan · Md. Shahriar Karim
Abstract:
Information transmission by diffusing particles is crucial in many biophysical and artificial systems. In diffusive transport, what makes an optimal model choice in a given context remains elusive and vital in narrowing the search space for optimal model search in context-specific applications. This study explores a class of diffusion-reaction paradigms on different performance objectives. Precisely, we compare the robustness, characteristic length scale, and stochastic variability of the competing transport models considering the mesoscopic and microscopic views of the transport--asking whether the entrapment of diffusing molecules improves the reliability of the diffusive transport models.
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