372 citations · 849 across the 97 of their papers we have counts for
3 papers · 1 filter
Hybrid Backpropagation Parallel Reservoir Networks
Matthew Evanusa, Snehesh Shrestha, Michelle Girvan +2
In many real-world applications, fully-differentiable RNNs such as LSTMs and GRUs have been widely deployed to solve time series learning tasks. These networks train via Backpropag…
Deep Reservoir Networks with Learned Hidden Reservoir Weights using Direct Feedback Alignment
Matthew Evanusa, Cornelia Fermüller, Yiannis Aloimonos
Deep Reservoir Computing has emerged as a new paradigm for deep learning, which is based around the reservoir computing principle of maintaining random pools of neurons combined wi…
A Deep 2-Dimensional Dynamical Spiking Neuronal Network for Temporal Encoding trained with STDP
Matthew Evanusa, Cornelia Fermuller, Yiannis Aloimonos
The brain is known to be a highly complex, asynchronous dynamical system that is highly tailored to encode temporal information. However, recent deep learning approaches to not tak…