5 citations · 12 across the 5 of their papers we have counts for
5 papers
Computation harvesting in road traffic dynamics
Hiroyasu Ando, T. Okamoto, H. Chang +2
Owing to recent advances in artificial intelligence and internet of things (IoT) technologies, collected big data facilitates high computational performance, while its computationa…
Reinforcement Learning with Convolutional Reservoir Computing
Hanten Chang, Katsuya Futagami
Recently, reinforcement learning models have achieved great success, mastering complex tasks such as Go and other games with higher scores than human players. Many of these models…
Road traffic reservoir computing
Hiroyasu Ando, Hanten Chang
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 physi…
Convolutional Reservoir Computing for World Models
Hanten Chang, Katsuya Futagami
Recently, reinforcement learning models have achieved great success, completing complex tasks such as mastering Go and other games with higher scores than human players. Many of th…
Effect of shapes of activation functions on predictability in the echo state network
Hanten Chang, Shinji Nakaoka, Hiroyasu Ando
We investigate prediction accuracy for time series of Echo state networks with respect to several kinds of activation functions. As a result, we found that some kinds of activation…