Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Continual Learning with Echo State Networks   Continual Learning (CL) refers to a learning setup where data is non
stationary and the model has to learn without forgetting existing knowledge.
The study of CL for sequential patterns revolves around trained recurrent
networks. In this work, instead, we introduce CL in the context of Echo State
Networks (ESNs), where the recurrent component is kept fixed. We provide the
first evaluation of catastrophic forgetting in ESNs and we highlight the
benefits in using CL strategies which are not applicable to trained recurrent
models. Our results confirm the ESN as a promising model for CL and open to its
use in streaming scenarios.

23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph