Autonomous mobile robots form an important research topic in the field of robotics due to their near-term applicability in the real world as domestic service robots. These robots ...
Eric A. Antonelo, Benjamin Schrauwen, Jan M. Van C...
Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability,...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
We shed light on the key ingredients of reservoir computing and analyze the contribution of the network dynamics to the spatial encoding of inputs. Therefore, we introduce attracto...
Reservoir Computing is a new paradigm for using Recurrent Neural Networks which shows promising results. However, as the recurrent part is created randomly, it typically needs to b...
Xavier Dutoit, Benjamin Schrauwen, Jan M. Van Camp...
Abstract. We approach the themes “computing with chaos” and “reservoir computing” in a unified setting. Different neural architectures are mentioned which display chaotic...
Training recurrent neural networks is hard. Recently it has however been discovered that it is possible to just construct a random recurrent topology, and only train a single linea...
Benjamin Schrauwen, David Verstraeten, Jan M. Van ...
— Many applications of Reservoir Computing (and other signal processing techniques) have to deal with information processing of signals with multiple time-scales. Classical Reser...
Francis Wyffels, Benjamin Schrauwen, David Verstra...
— In this work we tackle the road sign problem with Reservoir Computing (RC) networks. The T-maze task (a particular form of the road sign problem) consists of a robot in a T-sha...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...