9 citations · 16 across the 9 of their papers we have counts for
5 papers · 1 filter
Bayesian learning of adatom interactions from atomically-resolved imaging data
Mani Valleti, Qiang Zou, Rui Xue +8
Atomic structures and adatom geometries of surfaces encode information about the thermodynamics and kinetics of the processes that lead to their formation, and which can be capture…
Application of variational policy gradient to atomic-scale materials synthesis
Siyan Liu, Nikolay Borodinov, Lukas Vlcek +3
Atomic-scale materials synthesis via layer deposition techniques present a unique opportunity to control material structures and yield systems that display unique functional proper…
Investigating phase transitions from local crystallographic analysis based on machine learning of atomic environments
Rama K. Vasudevan, Maxim Ziatdinov, Lukas Vlcek +8
Traditionally, phase transitions are explored using a combination of macroscopic functional characterization and scattering techniques, providing insight into average properties an…
Off-the-shelf deep learning is not enough: parsimony, Bayes and causality
Rama K. Vasudevan, Maxim Ziatdinov, Lukas Vlcek +1
Deep neural networks ("deep learning") have emerged as a technology of choice to tackle problems in natural language processing, computer vision, speech recognition and gameplay, a…
Reconstruction of the lattice Hamiltonian models from the observations of microscopic degrees of freedom in the presence of competing interactions
Sai Mani Prudhvi Valleti, Lukas Vlcek, Maxim Ziatdinov +2
The emergence of scanning probe and electron beam imaging techniques have allowed quantitative studies of atomic structure and minute details of electronic and vibrational structur…