Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Reconstruction of the exit wave function is an important route to interpreting high-resolution
transmission electron microscopy (HRTEM) images. Here we demonstrate that convolutional …

Large, carefully partitioned datasets are essential to train neural networks and standardize
performance benchmarks. As a result, we have set up new repositories to make our electron …

The scientific and technological progresses of the chemical and materials science
disciplines lead to a significant amount of numerical and textual data stored in the published …

We present a computational imaging mode for large scale electron microscopy data, which
retrieves a complex wave from noisy/sparse intensity recordings using a deep learning …

This doctoral thesis covers some of my advances in electron microscopy with deep learning.
Highlights include a comprehensive review of deep learning in electron microscopy; large …

Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Figure numbers for a variety of two-dimensional tSNE visualisations are tabulated in table
S1 to ease comparison. Visualizations are for the first 50 principal components extracted by …