List of works - Maxim Ziatdinov

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

scientific article published in 2022

Bowl Inversion and Electronic Switching of Buckybowls on Gold

scientific article published on 24 August 2016

Bridging microscopy with molecular dynamics and quantum simulations: an atomAI based pipeline

scientific article published in 2022

Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study

scientific article published on 27 September 2019

Causal analysis of competing atomistic mechanisms in ferroelectric materials from high-resolution scanning transmission electron microscopy data

scientific article published in 2020

Chemically induced topological zero mode at graphene armchair edges.

scientific article published on 31 January 2017

Data mining graphene: correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

scientific article

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations.

scientific article

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform.

scientific article

Deep data mining in a real space: separation of intertwined electronic responses in a lightly doped BaFe2As2.

scientific article

Deep kernel methods learn better: from cards to process optimization

scientific article published in 2024

Disentangling ferroelectric domain wall geometries and pathways in dynamic piezoresponse force microscopy via unsupervised machine learning

scientific article published in 2021

Exploration of lattice Hamiltonians for functional and structural discovery via Gaussian process-based exploration–exploitation

scientific article published in 2020

Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data

scientific article published on 11 December 2020

Fast Scanning Probe Microscopy via Machine Learning: Non-Rectangular Scans with Compressed Sensing and Gaussian Process Optimization

scientific article published on 11 August 2020

Identifying local structural states in atomic imaging by computer vision

scientific article (publication date: 2017)

Learning from Imperfections: Predicting Structure and Thermodynamics from Atomic Imaging of Fluctuations

scientific article published on 10 January 2019

Machine learning in scanning transmission electron microscopy

scientific article published on 03 March 2022

Phases and Interfaces from Real Space Atomically Resolved Data: Physics-Based Deep Data Image Analysis.

scientific article

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

scientific article published on 11 December 2020

Role of edge geometry and chemistry in the electronic properties of graphene nanostructures

scientific article published on 01 January 2014

Toward Decoding the Relationship between Domain Structure and Functionality in Ferroelectrics via Hidden Latent Variables

scientific article published on 04 January 2021

Toward Electrochemical Studies on the Nanometer and Atomic Scales: Progress, Challenges, and Opportunities

scientific article published on 16 September 2019

Tracking atomic structure evolution during directed electron beam induced Si-atom motion in graphene via deep machine learning

scientific article published on 15 September 2020

List of works by Maxim Ziatdinov

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

Bowl Inversion and Electronic Switching of Buckybowls on Gold

Bridging microscopy with molecular dynamics and quantum simulations: an atomAI based pipeline

Building and exploring libraries of atomic defects in graphene: Scanning transmission electron and scanning tunneling microscopy study

Causal analysis of competing atomistic mechanisms in ferroelectric materials from high-resolution scanning transmission electron microscopy data

Chemically induced topological zero mode at graphene armchair edges.

Data mining graphene: correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations.

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform.

Deep data mining in a real space: separation of intertwined electronic responses in a lightly doped BaFe2As2.

Deep kernel methods learn better: from cards to process optimization

Disentangling ferroelectric domain wall geometries and pathways in dynamic piezoresponse force microscopy via unsupervised machine learning

Exploration of lattice Hamiltonians for functional and structural discovery via Gaussian process-based exploration–exploitation

Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data

Fast Scanning Probe Microscopy via Machine Learning: Non-Rectangular Scans with Compressed Sensing and Gaussian Process Optimization

Identifying local structural states in atomic imaging by computer vision

Learning from Imperfections: Predicting Structure and Thermodynamics from Atomic Imaging of Fluctuations

Machine learning in scanning transmission electron microscopy

Phases and Interfaces from Real Space Atomically Resolved Data: Physics-Based Deep Data Image Analysis.

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

Role of edge geometry and chemistry in the electronic properties of graphene nanostructures

Toward Decoding the Relationship between Domain Structure and Functionality in Ferroelectrics via Hidden Latent Variables

Toward Electrochemical Studies on the Nanometer and Atomic Scales: Progress, Challenges, and Opportunities

Tracking atomic structure evolution during directed electron beam induced Si-atom motion in graphene via deep machine learning