Maximum entropy methods for extracting the learned features of deep neural networks

Volume: 13, Issue: 10, Pages: e1005836 - e1005836
Published: Oct 30, 2017
Abstract
New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method...
Paper Details
Title
Maximum entropy methods for extracting the learned features of deep neural networks
Published Date
Oct 30, 2017
Volume
13
Issue
10
Pages
e1005836 - e1005836
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