Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Transfer Learning in Brain-Computer Interfaces with Adversarial
  Variational Autoencoders   We introduce adversarial neural networks for representation learning as a
novel approach to transfer learning in brain-computer interfaces (BCIs). The
proposed approach aims to learn subject-invariant representations by
simultaneously training a conditional variational autoencoder (cVAE) and an
adversarial network. We use shallow convolutional architectures to realize the
cVAE, and the learned encoder is transferred to extract subject-invariant
features from unseen BCI users' data for decoding. We demonstrate a
proof-of-concept of our approach based on analyses of electroencephalographic
(EEG) data recorded during a motor imagery BCI experiment.

12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th