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OverviewSymmetric functions, which take as input an unordered, fixed-size s et, find practical application in myriad physical settings based on indistinguishable points or particles, and are also used as intermediate building blocks to construct networks with other invariances. Symmetric functions are known to be universally representable by neural networks that enforce permutation invariance. However the theoretical tools that characterize the approximation, optimization and generalization of typical networks fail to adequately characterize architectures that enforce invariance. Full Product DetailsAuthor: Seymour L PurvisPublisher: Scholastic Singapore Imprint: Scholastic Singapore Dimensions: Width: 15.20cm , Height: 0.80cm , Length: 22.90cm Weight: 0.200kg ISBN: 9789810898106ISBN 10: 981089810 Pages: 142 Publication Date: 13 March 2024 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: In stock  We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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