neural-architecture-search

Activation Function Synthesis

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Adaptive hybrid activation function for deep neural networks

Y. Bodyanskiy, Serhii Kostiuk•Sun Apr 24 2022

The adaptive hybrid activation function (AHAF) is proposed that combines the properties of the rectifier units and the squashing functions and provides high performance for the neural network training process.

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Learnable Extended Activation Function for Deep Neural Networks

Serhii Kostiuk, Yevgeniy V. Bodyanskiy•Sat Sep 30 2023

An adaptive activation function that combines the properties of squashing functions and rectifier units that can directly replace SiLU, ReLU, Sigmoid, Tanh, Swish, and AHAF in feed-forward, recurrent, and many other neural network architectures.

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