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A Practical Guide to Applying Echo State Networks
TLDR
Practical techniques and recommendations for successfully applying Echo State Network, as well as some more advanced application-specific modifications are presented.
Reservoir Computing Trends
TLDR
A brief introduction into basic concepts, methods, insights, current developments, and some applications of RC are given.
Overview of Reservoir Recipes
TLDR
This report motivates the new definition of the paradigm and surveys the reservoir generation/adaptation techniques, offering a natural conceptual classification which transcends boundaries of the current "brand-names" of reservoir methods.
Reservoir Computing and Self-Organized Neural Hierarchies
TLDR
This thesis overviews existing and investigates new alternatives to the classical supervised training of RNNs and their hierarchies and proposes and investigates the use of two different neural network models for the reservoirs together with several unsupervised adaptation techniques, as well as un supervisedly layer-wise trained deep hierarchies of such models.
Time Warping Invariant Echo State Networks
TLDR
This report presents a modification of ESNs - time warping invariant echo state networks (TWIESNs) that can effectively deal with time warped in dynamic pattern recognition.
Echo State Networks with Trained Feedbacks
TLDR
This report explores possible directions in which the theoretical findings could be applied to increase the computational power of Echo State Networks and proposes a modification of ESNs called Layered ESNs.
On self-organizing reservoirs and their hierarchies
TLDR
This work demonstrates in a rigorous way the advantage of using the self-organizing reservoirs over the traditional random ones and using hierarchies of such over single reservoirs with a synthetic handwriting-like temporal pattern recognition dataset.
Overview of Reservoir Recipes A survey of new RNN training methods that follow the Reservoir paradigm
TLDR
The new definition of the paradigm is motivated and the reservoir generation/adaptation techniques are surveyed, offering a natural conceptual classification which transcends boundaries of the current " brand-names " of reservoir methods.
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