scholarly journals Machine Learning of Dynamic Electron Correlation Energies from Topological Atoms

2017 ◽  
Vol 14 (1) ◽  
pp. 216-224 ◽  
Author(s):  
James L. McDonagh ◽  
Arnaldo F. Silva ◽  
Mark A. Vincent ◽  
Paul L. A. Popelier
Keyword(s):  
Machine Learning ◽  
Electron Correlation ◽  
Topological Atoms

scholarly journals Machine learning electron correlation in a disordered medium

2019 ◽  
Vol 99 (8) ◽  
Author(s):  
Jianhua Ma ◽  
Puhan Zhang ◽  
Yaohua Tan ◽  
Avik W. Ghosh ◽  
Gia-Wei Chern
Keyword(s):  
Machine Learning ◽  
Electron Correlation ◽  
Disordered Medium

Mind wandering as data augmentation: How mental travel supports abstraction

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Mental Content ◽  
Mind Wandering ◽  
Theoretical Framework ◽  
Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

To What Extent are Inelastically Scattered Electrons Useful in the Stem?

1973 ◽  
Vol 31 ◽  
pp. 286-287 ◽  
Author(s):  
H. Rose
Keyword(s):  
Electron Microscope ◽  
High Resolution ◽  
Electron Correlation ◽  
Quantum Noise ◽  
Collection Efficiency ◽  
Scanning Transmission Electron Microscope ◽  
Electron Cloud ◽  
Scanning Time ◽  
Transmission Electron ◽  
Scanning Transmission

The scanning transmission electron microscope offers the possibility of utilizing inelastically scattered electrons. Use of these electrons in addition to the elastically scattered electrons should reduce the scanning time (dose) Which is necessary to keep the quantum noise below a certain level. Hence it should lower the radiation damage. For high resolution, Where the collection efficiency of elastically scattered electrons is small, the use of Inelastically scattered electrons should become more and more favorable because they can all be detected by means of a spectrometer. Unfortunately, the Inelastic scattering Is a non-localized interaction due to the electron-electron correlation, occurring predominantly at the circumference of the atomic electron cloud.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Mathematics for Machine Learning

2020 ◽  
Author(s):  
Marc Peter Deisenroth ◽  
A. Aldo Faisal ◽  
Cheng Soon Ong
Keyword(s):  
Machine Learning

Phase Transitions in Machine Learning

2009 ◽  
Author(s):  
Lorenza Saitta ◽  
Attilio Giordana ◽  
Antoine Cornuejols
Keyword(s):  
Machine Learning ◽  
Phase Transitions

Understanding Machine Learning

2009 ◽  
Author(s):  
Shai Shalev-Shwartz ◽  
Shai Ben-David
Keyword(s):  
Machine Learning
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