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Jeffrey Ede

I'm a physics PhD student developing new approaches to enhance TEM and STEM signals with machine learning. My supervisor is Jeremy Sloan.

Research Articles:

Ede, J.M., 2020. Review: Deep Learning in Electron Microscopy. arXiv preprint arXiv:2009.08328. https://arxiv.org/abs/2009.08328

Ede, J.M., 2020. Warwick Electron Microscopy Datasets. Machine Learning: Science and Technology, 1(4), p. 045003. https://doi.org/10.1088/2632-2153/ab9c3c

Ede, J.M. and Beanland, R., 2020. Partial Scanning Transmission Electron Microscopy with Deep Learning. Scientific Reports, 10, p. 8332. https://doi.org/10.1038/s41598-020-65261-0

Ede, J.M. and Beanland, R., 2020. Adaptive Learning Rate Clipping Stabilizes Learning. Machine Learning: Science and Technology, 1(1), p. 015011. https://doi.org/10.1088/2632-2153/ab81e2

Ede, J.M. and Beanland, R., 2019. Improving Electron Micrograph Signal-to-Noise with an Atrous Convolutional Encoder-Decoder. Ultramicroscopy, 202, pp.18-25. https://doi.org/10.1016/j.ultramic.2019.03.017

Ede, J.M., Peters, J.J., Sloan, J. and Beanland, R., 2020. Exit Wavefunction Reconstruction from Single Transmission Electron Micrographs with Deep Learning. arXiv preprint arXiv:2001.10938. https://arxiv.org/abs/2001.10938

Ede, J.M., 2019. Deep Learning Supersampled Scanning Transmission Electron Microscopy. arXiv preprint arXiv:1910.10467. https://arxiv.org/abs/1910.10467

Ede, J.M., 2020. Adaptive Partial Scanning Transmission Electron Microscopy with Reinforcement Learning. arXiv preprint arXiv:2004.02786. https://arxiv.org/abs/2004.02786

Ede, J.M., 2018. Autoencoders, Kernels, and Multilayer Perceptrons for Electron Micrograph Restoration and Compression. arXiv preprint arXiv:1808.09916. https://arxiv.org/abs/1808.09916

You can see more of my work on GitHub. Datasets have been moved here.

For additional information, feel free to contact me. I'm happy to give advice or review the occasional paper.