DOAJ Open Access 2023

Learning Circular Hidden Quantum Markov Models: A Tensor Network Approach

Mohammad Ali Javidian Vaneet Aggarwal Zubin Jacob

Abstrak

This article proposes circular hidden quantum Markov models (c-HQMMs), which can be applied for modeling temporal data. We show that c-HQMMs are equivalent to a tensor network (more precisely, circular local purified state) model. This equivalence enables us to provide an efficient learning model for c-HQMMs. The proposed learning approach is evaluated on six real datasets and demonstrates the advantage of c-HQMMs as compared to HQMMs and HMMs.

Topik & Kata Kunci

Atomic physics. Constitution and properties of matter Materials of engineering and construction. Mechanics of materials

Penulis (3)

Mohammad Ali Javidian

Vaneet Aggarwal

Zubin Jacob

Format Sitasi

APA MLA BibTeX

Javidian, M.A., Aggarwal, V., Jacob, Z. (2023). Learning Circular Hidden Quantum Markov Models: A Tensor Network Approach. https://doi.org/10.1109/TQE.2023.3319254

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Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.1109/TQE.2023.3319254
Akses: Open Access ✓