73 citations · 288 across the 10 of their papers we have counts for
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physics.comp-ph2020★ 73 cited
Learning physical properties of liquid crystals with deep convolutional neural networks
Higor Y. D. Sigaki, Ervin K. Lenzi, Rafael S. Zola +2
Machine learning algorithms have been available since the 1990s, but it is much more recently that they have come into use also in the physical sciences. While these algorithms hav…
physics.comp-ph2014★ 33 cited
Investigating the interplay between mechanisms of anomalous diffusion via fractional Brownian walks on a comb-like structure
H. V. Ribeiro, A. A. Tateishi, L. G. A. Alves +2
The comb model is a simplified description for anomalous diffusion under geometric constraints. It represents particles spreading out in a two-dimensional space where the motions i…