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
Tim Albrecht, Gregory Slabaugh, Eduardo Alonso, and SM Masudur R. Al-Arif.
Nanotechnology, 28(42), 423001, 2017
- Unsupervised vector-based classification of single-molecule charge transport data
Mario Lemmer, Michael S. Inkpen, Katja Kornysheva, Nicholas J. Long, and Tim Albrecht.
Nature Communications, 7, 1–10, 2016