Computing & Internet      Computer Science

Symmetric Neural Networks Theory

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Book Details
Language
English
Publishers
shetty publishers (13 Mar. 2024)
Weight
0.2 KG
Publication Date
13/03/2024
ISBN-10
981089810X
Pages
142 pages
ISBN-13
9789810898106
Dimensions
15.24 x 0.76 x 22.86 cm
SKU
9789810898106
Author Name
Seymour L. Purvis (Author)
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Symmetric 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 functionsare 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. .

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