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This page will be updated with publication links discussed during both sessions August 11 & August 13.
This page will be updated with publication links discussed during both sessions August 11 & August 13.
If you would like to add to or modify any of the publications posted below, please email altaylor@lbl.gov.
SESSION TUESDAY, AUGUST 11
SESSION TUESDAY, AUGUST 11
From Alex Hexemer:
From Tess Smidt:
e3nn Code (PyTorch) - link here
e3nn_tutorial - link here
Tensor Field Networks (arXiv:1802.08219)
3D Steerable CNNs (arXiv:1807.02547)
[NEW!] Finding symmetry breaking order parameters with Euclidean Neural Networks T. E. Smidt, M. Geiger, B. K. Miller (arXiv:2007.02005)
From Daniela Ushizima:
From Mathew Cherukara
Wendy Di on using XRF data to accelerate tomographic reconstruction - link here
BCDINN and PtychoNN papers - link here
SESSION THURSDAY, AUGUST 13
SESSION THURSDAY, AUGUST 13
From Marcus Noack:
GP autonomous experiment papers - link here. Code is available by contacting MarcusNoack@lbl.gov.
From Sergei Kalinin:
GPim: Python package that provides an easy way to apply Gaussian processes (GP) - https://github.com/ziatdinovmax/GPim
AtomAI: Python package for machine learning-based analysis of experimental atom-resolved data from electron and scanning probe microscopes - https://github.com/ziatdinovmax/atomai
AI Crystallographer: https://github.com/pycroscopy/AICrystallographer
PyCroscopy: Python package for image processing and scientific analysis of imaging modalities such as multi-frequency scanning probe microscopy, scanning tunneling spectroscopy, x-ray diffraction microscopy, and transmission electron microscopy. - https://github.com/pycroscopy/pycroscopy
From Stephen Whitelam:
Whitelam, Stephen, and Isaac Tamblyn. "Learning to grow: Control of material self-assembly using evolutionary reinforcement learning." Physical Review E 101.5 (2020): 052604 - link here
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