Northwestern University

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Filtering by: Keyword Interpretable Machine Learning Resource type Dissertation Subject Computational chemistry

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Interpretable Machine Learning with Applications to Computational Materials Science

Description:

Machine learning and deep learning have been proven successful across various scientific fields, such as computer vision, natural language processing, and recommendation systems. As models become more complex, with more parameters and intricate architectures, they can achieve higher prediction accuracy when trained on larger datasets. However, despite the great prediction...

Keyword:

Neural Network, Interpretable Machine Learning, and Function Visualization

Subject:

Statistics and Computational chemistry

Creator:

Zhang, Shengtong

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

08/23/2023

Date Created:

2023-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_995408 and http://dissertations.umi.com/northwestern:16632