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Maxim Ziatdinov

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Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities

Feb 20, 2024
Arpan Biswas, Sai Mani Prudhvi Valleti, Rama Vasudevan, Maxim Ziatdinov, Sergei V. Kalinin

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Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy

Oct 08, 2023
Sergei V. Kalinin, Yongtao Liu, Arpan Biswas, Gerd Duscher, Utkarsh Pratiush, Kevin Roccapriore, Maxim Ziatdinov, Rama Vasudevan

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Towards Lightweight Data Integration using Multi-workflow Provenance and Data Observability

Aug 17, 2023
Renan Souza, Tyler J. Skluzacek, Sean R. Wilkinson, Maxim Ziatdinov, Rafael Ferreira da Silva

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Combining Variational Autoencoders and Physical Bias for Improved Microscopy Data Analysis

Feb 08, 2023
Arpan Biswas, Maxim Ziatdinov, Sergei V. Kalinin

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Microscopy is All You Need

Oct 12, 2022
Sergei V. Kalinin, Rama Vasudevan, Yongtao Liu, Ayana Ghosh, Kevin Roccapriore, Maxim Ziatdinov

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Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach

Jun 30, 2022
Arpan Biswas, Rama Vasudevan, Maxim Ziatdinov, Sergei V. Kalinin

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Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning

May 30, 2022
Maxim Ziatdinov, Yongtao Liu, Kyle Kelley, Rama Vasudevan, Sergei V. Kalinin

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Active learning in open experimental environments: selecting the right information channel(s) based on predictability in deep kernel learning

Mar 18, 2022
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

Jun 23, 2021
Maxim Ziatdinov, Chun Yin Wong, Sergei V. Kalinin

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Semi-supervised learning of images with strong rotational disorder: assembling nanoparticle libraries

May 24, 2021
Maxim Ziatdinov, Muammer Yusuf Yaman, Yongtao Liu, David Ginger, Sergei V. Kalinin

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