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Found 3 papers, 0 papers with code
Unsupervised learning of site percolation based on shuffled configurations
In the field of statistical physics, machine learning has gained significant popularity and has achieved remarkable results in recent studies on phase transitions. In this paper, we apply Principal Component Analysis (PCA) and Autoencoder(AE) based on Unsupervised learning to study the various configurations of the percolation model in equilibrium phase transition.
Transfer learning of phase transitions in percolation and directed percolation
With the DANN, only a small fraction of input configurations (2d images) needs to be labeled, which is automatically chosen, in order to capture the critical point.
Vis-TOP: Visual Transformer Overlay Processor
Vis-TOP summarizes the characteristics of all visual Transformer models and implements a three-layer and two-level transformation structure that allows the model to be switched or changed freely without changing the hardware architecture.
