Search Results for author: Rama K. Vasudevan

Found 10 papers, 7 papers with code

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

1 code implementation20 Apr 2021 Yongtao Liu, Rama K. Vasudevan, Kyle Kelley, Dohyung Kim, Yogesh Sharma, Mahshid Ahmadi, Sergei V. Kalinin, Maxim Ziatdinov

A shift-invariant variational autoencoder (shift-VAE) is developed as an unsupervised method for the analysis of spectral data in the presence of shifts along the parameter axis, disentangling the physically-relevant shifts from other latent variables.

Denoising Dimensionality Reduction

Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy

no code implementations22 Mar 2021 Sergei V. Kalinin, Maxim A. Ziatdinov, Jacob Hinkle, Stephen Jesse, Ayana Ghosh, Kyle P. Kelley, Andrew R. Lupini, Bobby G. Sumpter, Rama K. Vasudevan

Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with domain applications ranging from theory and materials prediction to high-throughput data analysis.

Autonomous Driving Decision Making +1

Autonomous Experiments in Scanning Probe Microscopy and Spectroscopy: Choosing Where to Explore Polarization Dynamics in Ferroelectrics

1 code implementation25 Nov 2020 Rama K. Vasudevan, Kyle Kelley, Hiroshi Funakubo, Stephen Jesse, Sergei V. Kalinin, Maxim Ziatdinov

Polarization dynamics in ferroelectric materials are explored via the automated experiment in Piezoresponse Force Spectroscopy.

Disordered Systems and Neural Networks Data Analysis, Statistics and Probability

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

no code implementations4 May 2020 Rama K. Vasudevan, Maxim Ziatdinov, Lukas Vlcek, Sergei V. Kalinin

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, and in just a few years has led to superhuman level performance and ushered in a new wave of "AI."

speech-recognition Speech Recognition

Guided search for desired functional responses via Bayesian optimization of generative model: hysteresis loop shape engineering in ferroelectrics

2 code implementations27 Apr 2020 Sergei V. Kalinin, Maxim Ziatdinov, Rama K. Vasudevan

Here we suggest and implement a Gaussian Process based methods that allow to effectively sample the degenerate parameter space of a complex non-local model to output regions of parameter space which yield desired functionalities.

Disordered Systems and Neural Networks Materials Science Computational Physics

Exploration of lattice Hamiltonians for functional and structural discovery via Gaussian Process-based Exploration-Exploitation

1 code implementation9 Apr 2020 Sergei V. Kalinin, Mani Valleti, Rama K. Vasudevan, Maxim Ziatdinov

Statistical physics models ranging from simple lattice to complex quantum Hamiltonians are one of the mainstays of modern physics, that have allowed both decades of scientific discovery and provided a universal framework to understand a broad range of phenomena from alloying to frustrated and phase-separated materials to quantum systems.

Materials Science Computational Physics

Imaging Mechanism for Hyperspectral Scanning Probe Microscopy via Gaussian Process Modelling

2 code implementations26 Nov 2019 Maxim Ziatdinov, Dohyung Kim, Sabine Neumayer, Rama K. Vasudevan, Liam Collins, Stephen Jesse, Mahshid Ahmadi, Sergei V. Kalinin

We investigate the ability to reconstruct and derive spatial structure from sparsely sampled 3D piezoresponse force microcopy data, captured using the band-excitation (BE) technique, via Gaussian Process (GP) methods.

Computational Physics Materials Science

USID and Pycroscopy -- Open frameworks for storing and analyzing spectroscopic and imaging data

1 code implementation22 Mar 2019 Suhas Somnath, Chris R. Smith, Nouamane Laanait, Rama K. Vasudevan, Anton Ievlev, Alex Belianinov, Andrew R. Lupini, Mallikarjun Shankar, Sergei V. Kalinin, Stephen Jesse

The second is Pycroscopy, which provides algorithms for scientific analysis of nanoscale imaging and spectroscopy modalities and is built on top of pyUSID and USID.

Data Analysis, Statistics and Probability

Deep Learning Analysis of Defect and Phase Evolution During Electron Beam Induced Transformations in WS2

no code implementations14 Mar 2018 Artem Maksov, Ondrej Dyck, Kai Wang, Kai Xiao, David B. Geohegan, Bobby G. Sumpter, Rama K. Vasudevan, Stephen Jesse, Sergei V. Kalinin, Maxim Ziatdinov

Understanding elementary mechanisms behind solid-state phase transformations and reactions is the key to optimizing desired functional properties of many technologically relevant materials.

Materials Science

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