Neural Network Architectures and Activation Functions: A Gaussian Process Approach
Overview & Synopsis
Determining the right architecture is a computationally intensive process, requiring many trials with different candidate architectures. We show that the neural activation function, if allowed to individually change for each neuron, can implicitly control many aspects of the network architecture.
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Document Information
| Document Title | Neural Network Architectures and Activation Functions: A Gaussian Process Approach |
|---|---|
| Author / Organization | Sebastian Urban |
| Subject & Discipline | Neural Networks, Deep Learning, Artificial Intelligence, Machine Learning, and Logic Programming, Algorithms and Data Structures |
| Categories | Neural Networks |
| Publication Year | 2017 |
| Resource Verification | ✓ Verified Direct PDF Available |
| Original Host Website |
FreeComputerBooks.com
(freecomputerbooks.com)
|
| File Format | application/pdf (Portable Document Format) |
| Reported File Size | -0 KB (-1 bytes) |
| Language | ENGLISH |
| Catalog ID | DOC-108455 |
| Original Source Link | Visit Source Page on freecomputerbooks.com » |