Maxim Ziatdinov | DeepAI

DeepAI AI Chat

Featured Co-authors

Rafael Ferreira da Silva
21 publications
Sergei V. Kalinin
20 publications
Dohyung Kim
14 publications
Renan Souza
11 publications
Yongtao Liu
9 publications
Ayana Ghosh
6 publications
Sean R. Wilkinson
5 publications
Rama K. Vasudevan
5 publications
Anees Al-Najjar
4 publications
Debangshu Mukherjee
4 publications
Ondrej Dyck
4 publications

∙ 08/17/2023

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

Modern large-scale scientific discovery requires multidisciplinary colla...

0 Renan Souza, et al. ∙

∙ 07/12/2023

Cyber Framework for Steering and Measurements Collection Over Instrument-Computing Ecosystems

We propose a framework to develop cyber solutions to support the remote ...

0 Anees Al-Najjar, et al. ∙

∙ 02/08/2023

Combining Variational Autoencoders and Physical Bias for Improved Microscopy Data Analysis

Electron and scanning probe microscopy produce vast amounts of data in t...

0 Arpan Biswas, et al. ∙

∙ 10/18/2022

Enabling Autonomous Electron Microscopy for Networked Computation and Steering

Advanced electron microscopy workflows require an ecosystem of microscop...

0 Anees Al-Najjar, et al. ∙

∙ 10/12/2022

Microscopy is All You Need

We pose that microscopy offers an ideal real-world experimental environm...

0 Sergei V. Kalinin, et al. ∙

∙ 06/30/2022

Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach

Unsupervised and semi-supervised ML methods such as variational autoenco...

37 Arpan Biswas, et al. ∙

∙ 05/30/2022

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

Recent progress in machine learning methods, and the emerging availabili...

0 Maxim Ziatdinov, et al. ∙

∙ 03/18/2022

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

Active learning methods are rapidly becoming the integral component of a...

0 Maxim Ziatdinov, et al. ∙

∙ 06/23/2021

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders

Recent advances in scanning tunneling and transmission electron microsco...

0 Maxim Ziatdinov, et al. ∙

∙ 05/24/2021

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

The proliferation of optical, electron, and scanning probe microscopies ...

17 Maxim Ziatdinov, et al. ∙

∙ 05/16/2021

AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond

AtomAI is an open-source software package bridging instrument-specific P...

12 Maxim Ziatdinov, et al. ∙

∙ 04/20/2021

Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy

A shift-invariant variational autoencoder (shift-VAE) is developed as an...

0 Yongtao Liu, et al. ∙

∙ 04/20/2021

Robust Feature Disentanglement in Imaging Data via Joint Invariant Variational Autoencoders: from Cards to Atoms

Recent advances in imaging from celestial objects in astronomy visualize...

20 Maxim Ziatdinov, et al. ∙

∙ 01/21/2021

Ensemble learning and iterative training (ELIT) machine learning: applications towards uncertainty quantification and automated experiment in atom-resolved microscopy

Deep learning has emerged as a technique of choice for rapid feature ext...

6 Ayana Ghosh, et al. ∙

∙ 05/04/2020

Off-the-shelf deep learning is not enough: parsimony, Bayes and causality

Deep neural networks ("deep learning") have emerged as a technology of c...

0 Rama K. Vasudevan, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world