Search Results for author:
Found 4 papers, 1 papers with code
Leveraging Product as an Activation Function in Deep Networks
We present windowed product unit neural networks (WPUNNs), a simple method of leveraging product as a nonlinearity in a neural network.
A parameterized activation function for learning fuzzy logic operations in deep neural networks
We present a deep learning architecture for learning fuzzy logic expressions.
Neural Decomposition of Time-Series Data for Effective Generalization
We present a neural network technique for the analysis and extrapolation of time-series data called Neural Decomposition (ND).
A continuum among logarithmic, linear, and exponential functions, and its potential to improve generalization in neural networks
We present the soft exponential activation function for artificial neural networks that continuously interpolates between logarithmic, linear, and exponential functions.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
