Activation Function Synthesis
3 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Most implemented papers
Adaptive hybrid activation function for deep neural networks
s-kostyuk/ahaf_activation_pytorch
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System research and information technologies 2022
The proposed function can be used as a drop-in replacement for ReLU, SiL and Swish activations for deep neural networks and can evolve to one of such functions during the training.
Deep neural network based on F-neurons and its learning
s-kostyuk/f-neuron
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Research Square (pre-print) 2022
Deep neural networks often employ piece-wise activation functions like ReLU to overcome the effects of exploding and vanishing gradients.
Learnable Extended Activation Function (LEAF) for Deep Neural Networks
s-kostyuk/leaf-aaf
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International Journal of Computing 2023
This paper introduces Learnable Extended Activation Function (LEAF) - an adaptive activation function that combines the properties of squashing functions and rectifier units.
