| AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy M Ziatdinov, A Ghosh, CYT Wong, SV Kalinin Nature Machine Intelligence, 1-12, 2022 | 107* | 2022 |
| Disentangling ferroelectric wall dynamics and identification of pinning mechanisms via deep learning Y Liu, R Proksch, CY Wong, M Ziatdinov, SV Kalinin Advanced Materials 33 (43), 2103680, 2021 | 33 | 2021 |
| Understanding effects of chemical complexity on helium bubble formation in Ni-based concentrated solid solution alloys based on elemental segregation measurements X Wang, K Jin, CY Wong, D Chen, H Bei, Y Wang, M Ziatdinov, WJ Weber, ... Journal of Nuclear Materials 569, 153902, 2022 | 9 | 2022 |
| Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders M Ziatdinov, CYT Wong, SV Kalinin Machine Learning: Science and Technology 4 (4), 045033, 2023 | 3 | 2023 |
| Comparing U-Net and Mask R-CNN Algorithms for Deep Learning-Based Segmentation of Electron Microscopy Images containing cavities for Nuclear Reactor Applications S Agarwal, A Sawant, T Wong, SE Copp, J Reyes-Zacarias, SJ Zinkle 2023 3rd International Conference on Electrical, Computer, Communications …, 2023 | 3 | 2023 |
| Deep Learning–Based Workflow for Analyzing Helium Bubbles in Transmission Electron Microscopy Images CY Wong, X Wang, Z Fan, K More, S Kalinin, M Ziatdinov Microscopy and Microanalysis 27 (S1), 2132-2133, 2021 | | 2021 |
