Knowledge Guided Machine Learning : Accelerating Discovery using Scientific Knowledge and Data.

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Bibliographic Details
Imprint:Boca Raton, FL : CRC Press, 2023.
©2023
Description:1 online resource ( xii, 430 pages.)
Language:English
Series:Chapman & Hall/CRC data mining and knowledge discovery series
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12960126
Hidden Bibliographic Details
Other authors / contributors:Karpatne, Anuj, editor.
Kannan, Ramakrishnan, editor.
Kumar, Vipin, 1956- editor.
ISBN:9781003143376
1003143377
9781000598100
1000598101
9781000598131
1000598136
9780367698201
9780367693411
Notes:Includes bibliographical references and index.
Anuj Karpatne is an Assistant Professor in the Department of Computer Science at Virginia Tech. His research focuses on pushing on the frontiers of knowledge-guided machine learning by combining scientific knowledge and data in the design and learning of machine learning methods to solve scientific and societally relevant problems. Ramakrishnan Kannan is the group leader for Discrete Algorithms at Oak Ridge National Laboratory. His research expertise is in distributed machine learning and graph algorithms on HPC platforms and their application to scientific data with a specific interest for accelerating scientific discovery. Vipin Kumar is a Regents Professor at the University of Minnesota's Computer Science and Engineering Department. His current major research focus is on knowledge-guided machine learning and its applications to understanding the impact of human induced changes on the Earth and its environment.
Other form:Print version : 9780367693411
Standard no.:10.1201/9781003143376