Combining variational autoencoders and physical bias for improved microscopy data analysis by Arpan Biswas, Maxim Ziatdinov, Sergei V Kalinin

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Learning surface molecular structures via machine vision by Maxim Ziatdinov, Artem Maksov, Sergei V. Kalinin

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Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy by Kevin M. Roccapriore, Sergei V. Kalinin, Maxim Ziatdinov

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Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders by Mani Valleti, Maxim Ziatdinov, Yongtao Liu, Sergei V. Kalinin

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Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders by Maxim Ziatdinov, Chun Yin (Tommy) Wong, Sergei V Kalinin

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Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach by Arpan Biswas, Rama Vasudevan, Maxim Ziatdinov, Sergei V Kalinin

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Off-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality by Rama K. Vasudevan, Maxim Ziatdinov, Lukas Vlcek, Sergei V. Kalinin

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Autonomous convergence of STM control parameters using Bayesian optimization by Ganesh Narasimha, Saban Hus, Arpan Biswas, Rama Vasudevan, Maxim Ziatdinov

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Gaussian process analysis of electron energy loss spectroscopy data: multivariate reconstruction and kernel control by Sergei V. Kalinin, Andrew R. Lupini, Rama K. Vasudevan, Maxim Ziatdinov

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Exploring Physics of Ferroelectric Domain Walls in Real Time: Deep Learning Enabled Scanning Probe Microscopy by Yongtao Liu, Kyle P. Kelley, Hiroshi Funakubo, Sergei V. Kalinin, Maxim Ziatdinov

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Bridging microscopy with molecular dynamics and quantum simulations: an atomAI based pipeline by Ayana Ghosh, Maxim Ziatdinov, Ondrej Dyck, Bobby G. Sumpter, Sergei V. Kalinin

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Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy by Ayana Ghosh, Bobby G. Sumpter, Ondrej Dyck, Sergei V. Kalinin, Maxim Ziatdinov

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Exploring the Evolution of Metal Halide Perovskites via Latent Representations of the Photoluminescent Spectra by Sheryl Sanchez, Yongtao Liu, Jonghee Yang, Sergei V. Kalinin, Maxim Ziatdinov, Mahshid Ahmadi

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Probe microscopy is all you need by Sergei V Kalinin, Rama Vasudevan, Yongtao Liu, Ayana Ghosh, Kevin Roccapriore, Maxim Ziatdinov

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Unsupervised machine learning discovery of structural units and transformation pathways from imaging data by Sergei V. Kalinin, Ondrej Dyck, Ayana Ghosh, Yongtao Liu, Bobby G. Sumpter, Maxim Ziatdinov

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Learning the right channel in multimodal imaging: automated experiment in piezoresponse force microscopy by Yongtao Liu, Rama K. Vasudevan, Kyle P. Kelley, Hiroshi Funakubo, Maxim Ziatdinov, Sergei V. Kalinin

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Deep learning ferroelectric polarization distributions from STEM data via with and without atom finding by Christopher T. Nelson, Ayana Ghosh, Mark Oxley, Xiaohang Zhang, Maxim Ziatdinov, Ichiro Takeuchi, Sergei V. Kalinin

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Probing atomic-scale symmetry breaking by rotationally invariant machine learning of multidimensional electron scattering by Mark P. Oxley, Maxim Ziatdinov, Ondrej Dyck, Andrew R. Lupini, Rama Vasudevan, Sergei V. Kalinin

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Computational scanning tunneling microscope image database by Kamal Choudhary, Kevin F. Garrity, Charles Camp, Sergei V. Kalinin, Rama Vasudevan, Maxim Ziatdinov, Francesca Tavazza

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Adaptive sampling for accelerating neutron diffraction-based strain mapping by S V Venkatakrishnan, Chris M Fancher, Maxim Ziatdinov, Rama Vasudevan, Kyle Saleeby, James Haley, Dunji Yu, Ke An, Alex Plotkowski

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