11 papers
Towards Self-Optimizing Electron Microscope: Robust Tuning of Aberration Coefficients via Physics-Aware Multi-Objective Bayesian Optimization
Utkarsh Pratiush, Austin Houston, Richard Liu +2
Realizing high-throughput aberration-corrected Scanning Transmission Electron Microscopy (STEM) exploration of atomic structures requires rapid tuning of multipole probe correctors…
Dynamic Multiband Microscopy: A Universal Paradigm for Quantitative Nanoscale Metrology
Boris N. Slautin, Alwikh Rohi, Sanjay Mathur +4
Scanning Probe Microscopy (SPM) is the primary tool for exploring nanoscale functionality, yet standard single-frequency operation is fundamentally limited, because the dynamic tip…
Rewards-based image analysis in microscopy
Kamyar Barakati, Yu Liu, Utkarsh Pratiush +2
Imaging and hyperspectral data analysis is central to progress across biology, medicine, chemistry, and physics. The core challenge lies in converting high-resolution or high-dimen…
DIVIDE: A Framework for Learning from Independent Multi-Mechanism Data Using Deep Encoders and Gaussian Processes
Vivek Chawla, Boris Slautin, Utkarsh Pratiush +2
Scientific datasets often arise from multiple independent mechanisms such as spatial, categorical or structural effects, whose combined influence obscures their individual contribu…
Reward driven discovery of the optimal microstructure representations with invariant variational autoencoders
Boris N. Slautin, Kamyar Barakati, Hiroshi Funakubo +4
Microscopy techniques generate vast amounts of complex image data that in principle can be used to discover simpler, interpretable, and parsimonious forms to reveal the underlying…
Attention-Based Explainability for Structure-Property Relationships
Boris N. Slautin, Utkarsh Pratiush, Yongtao Liu +4
Machine learning methods are emerging as a universal paradigm for constructing correlative structure-property relationships in materials science based on multimodal characterizatio…