Search Results for author:
Found 4 papers, 1 papers with code
Reinforcement Learning with Convolutional Reservoir Computing
The RCRC model uses a fixed random-weight CNN and a reservoir computing model to extract visual and time-series features.
Road traffic reservoir computing
Reservoir computing derived from recurrent neural networks is more applicable to real world systems than deep learning because of its low computational cost and potential for physical implementation.
Convolutional Reservoir Computing for World Models
Many of these models collect considerable data on the tasks and improve accuracy by extracting visual and time-series features using convolutional neural networks (CNNs) and recurrent neural networks, respectively.
Effect of shapes of activation functions on predictability in the echo state network
We investigate prediction accuracy for time series of Echo state networks with respect to several kinds of activation functions.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
