Index Catalog // Arch : Northwestern University Institutional Repository

Description:: Materials science has been central to human advancement since time immemorial. There has always been curiosity around studying the processes required to extract materials, examine their structure, and ultimately tailor their properties to meet human needs. Over the last few centuries, the ability to tailor material properties was driven by...
Keyword:: Gaussian Process, Mixed Variable Machine Learning, Data Centric Design, Multicriteria Optimization, and Microstructure
Subject:: Materials Science, Statistics, and Design
Creator:: Iyer, Akshay
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/02/2022
Date Created:: 2021-01-01
Resource Type:: Dissertation
Alternate Identifier:: etdadmin_upload_851800 and http://dissertations.umi.com/northwestern:15801

Description:: Supervised learning model is one of the most fundamental machine learning models. It can provide powerful capability of prediction by learning complex patterns hidden in many, sometimes thousands, predictors. It can also be used as a building block of other machine learning tasks, like unsupervised learning and reinforcement learning. Such...
Keyword:: Stochastic Microstructures, Fisher Score, Deep Learning, Machine Learning, Concept Drift, and Nonstationarity Analysis
Subject:: Materials Science, Statistics, and Computer science
Creator:: Zhang, Kungang
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/01/2021
Date Created:: 2020-01-01
Resource Type:: Dissertation
Alternate Identifier:: etdadmin_upload_765218 and http://dissertations.umi.com/northwestern:15297

Description:: The heart of computational materials science lies in providing fundamental insights and understanding of materials behavior and properties across different scales. The significance of this task is highlighted by the Materials Genome Initiative and the emergence of computational tools and frameworks such as materials by design, microstructure sensitive design, and...
Keyword:: random Process, Multiscale simulation, Microstructure, Gaussian process, and Uncertainty
Subject:: Materials Science, Statistics, and Mechanical engineering
Creator:: Bostanabad, Ramin
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 02/12/2020
Date Created:: 2019-01-01
Resource Type:: Dissertation
Alternate Identifier:: http://dissertations.umi.com/northwestern:14508 and etdadmin_upload_638165

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