The exploration and application of Machine Learning tools has become an underpinning theme in various aspects of our work, including dimensionality reduction techniques (PCA, MPVC, t-SNE), Autoencoders for unsupervised classification, Support Vector Machines, and Deep Learning methods such as Convolutional Neural Networks.

 

References

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   Nanotechnology, 28(42), , 2017
2. Unsupervised vector-based classification of single-molecule charge transport data
   M. Lemmer, M. S. Inkpen, K. Kornysheva, N. J. Long, and T. Albrecht.
   Nature Communications, 7, , 2016