Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An end-to-end trainable hybrid classical-quantum classifier   We introduce a hybrid model combining a quantum-inspired tensor network and a
variational quantum circuit to perform supervised learning tasks. This
architecture allows for the classical and quantum parts of the model to be
trained simultaneously, providing an end-to-end training framework. We show
that compared to the principal component analysis, a tensor network based on
the matrix product state with low bond dimensions performs better as a feature
extractor for the input data of the variational quantum circuit in the binary
and ternary classification of MNIST and Fashion-MNIST datasets. The
architecture is highly adaptable and the classical-quantum boundary can be
adjusted according the availability of the quantum resource by exploiting the
correspondence between tensor networks and quantum circuits.

31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph