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.
- Deep learning for single-molecule science
T. Albrecht, G. Slabaugh, E. Alonso, and S. M. M. R. Al-Arif.
Nanotechnology, 28(42), , 2017
- 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