Forecasting of in situ electron energy loss spectroscopy

Design of a graphical user interface for few-shot machine learning classification of electron microscopy data

(2022) Christina Doty et al.   COMPUTATIONAL MATERIALS SCIENCE

Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results

(2022) Sujan Ghimire et al.   Energies

Utilizing machine learning on freight transportation and logistics applications: A review

(2022) Kalliopi Tsolaki et al.   ICT Express

Time-series forecasting with deep learning: a survey

(2021) Bryan Lim et al.   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Machine Learning Pipeline for Segmentation and Defect Identification from High-Resolution Transmission Electron Microscopy Data

(2021) Catherine K. Groschner et al.   MICROSCOPY AND MICROANALYSIS

The data-driven future of high-energy-density physics

(2021) Peter W. Hatfield et al.   NATURE

Efficient few-shot machine learning for classification of EBSD patterns

(2021) Kevin Kaufmann et al.   Scientific Reports

Automated and Autonomous Experiments in Electron and Scanning Probe Microscopy

(2021) Sergei V. Kalinin et al.   ACS Nano

Deep Learning Segmentation of Complex Features in Atomic-Resolution Phase-Contrast Transmission Electron Microscopy Images

(2021) Robbie Sadre et al.   MICROSCOPY AND MICROANALYSIS

RapidEELS: machine learning for denoising and classification in rapid acquisition electron energy loss spectroscopy

(2021) Cassandra M. Pate et al.   Scientific Reports

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

(2021) Sarah Akers et al.   npj Computational Materials

Unveiling the Microscopic Origins of Phase Transformations: An in Situ TEM Perspective

(2020) Lei Yu et al.   CHEMISTRY OF MATERIALS

Asymmetric Lattice Disorder Induced at Oxide Interfaces

(2020) Steven R. Spurgeon et al.   Advanced Materials Interfaces

Machine Learning in Geo- and Environmental Sciences: From Small to Large Scale

(2020) Pejman Tahmasebi et al.   ADVANCES IN WATER RESOURCES

Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images

(2020) James P. Horwath et al.   npj Computational Materials

Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review

(2020) Samuel Lalmuanawma et al.   CHAOS SOLITONS & FRACTALS

Air Temperature Forecasting Using Machine Learning Techniques: A Review

(2020) Jenny Cifuentes et al.   Energies

Towards data-driven next-generation transmission electron microscopy

(2020) Steven R. Spurgeon et al.   NATURE MATERIALS

Order-disorder behavior at thin film oxide interfaces

(2020) Steven R. Spurgeon   CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE

A Systematic Review of Statistical and Machine Learning Methods for Electrical Power Forecasting with Reported MAPE Score

(2020) Eliana Vivas et al.   Entropy

A Systematic Review of Perception System and Simulators for Autonomous Vehicles Research

(2019) Francisca Rosique et al.   SENSORS

A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures

(2019) Yong Yu et al.   NEURAL COMPUTATION

Revealing ferroelectric switching character using deep recurrent neural networks

(2019) Joshua C. Agar et al.   Nature Communications

Atomic resolution convergent beam electron diffraction analysis using convolutional neural networks

(2019) Chenyu Zhang et al.   ULTRAMICROSCOPY

Forecasting stock market crisis events using deep and statistical machine learning techniques

(2018) Sotirios P. Chatzis et al.   EXPERT SYSTEMS WITH APPLICATIONS

A CFCC-LSTM Model for Sea Surface Temperature Prediction

(2018) Yuting Yang et al.   IEEE Geoscience and Remote Sensing Letters

A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns

(2018) W. Xu et al.   ULTRAMICROSCOPY

Machine learning at the energy and intensity frontiers of particle physics

(2018) Alexander Radovic et al.   NATURE

Direct Detection Electron Energy-Loss Spectroscopy: A Method to Push the Limits of Resolution and Sensitivity

(2017) James L. Hart et al.   Scientific Reports

Current status and future directions for in situ transmission electron microscopy

(2016) Mitra L. Taheri et al.   ULTRAMICROSCOPY

Frontiers of in situ electron microscopy

(2015) Haimei Zheng et al.   MRS BULLETIN

Hybrid Dynamic Optimization Methods for Systems Biology with Efficient Sensitivities

(2015) Nicholas Lewis et al.   Processes

The GIF Quantum, a next generation post-column imaging energy filter

(2010) Alexander Gubbens et al.   ULTRAMICROSCOPY