pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry
Quantum computing is a promising technology for machine learning, in terms of computational costs and outcomes. In this work, we intend to provide a framework that facilitates the use of quantum machine learning in the domain of brain-computer interfaces – where biomedical signals, such as brain wav...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Pensoft Publishers
2023-03-01
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| Series: | Research Ideas and Outcomes |
| Subjects: | |
| Online Access: | https://riojournal.com/article/101006/download/pdf/ |
| _version_ | 1797865860934664192 |
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| author | Anton Andreev Grégoire Cattan Sylvain Chevallier Quentin Barthélemy |
| author_facet | Anton Andreev Grégoire Cattan Sylvain Chevallier Quentin Barthélemy |
| author_sort | Anton Andreev |
| collection | DOAJ |
| description | Quantum computing is a promising technology for machine learning, in terms of computational costs and outcomes. In this work, we intend to provide a framework that facilitates the use of quantum machine learning in the domain of brain-computer interfaces – where biomedical signals, such as brain waves, are processed.To this end, we integrated Qiskit, a well-known quantum library, with pyRiemann, a framework for the analysis of biomedical signals using Riemannian Geometry. In this paper, we describe our approach, the main elements of our implementation and our research directions. A key result is the creation of a standardised pipeline (QuantumClassifierWithDefaultRiemannianPipeline) for the binary classification of brain waves. The git repository reported in this paper also contains a complete test suite and examples to guide practitioners. We believe that this software will enable further research on the joint field of brain-computer interfaces and quantum computing. |
| first_indexed | 2024-04-09T23:14:52Z |
| format | Article |
| id | doaj.art-0cc5055068674e8683098bfa9ce8e10b |
| institution | Directory Open Access Journal |
| issn | 2367-7163 |
| language | English |
| last_indexed | 2024-04-09T23:14:52Z |
| publishDate | 2023-03-01 |
| publisher | Pensoft Publishers |
| record_format | Article |
| series | Research Ideas and Outcomes |
| spelling | doaj.art-0cc5055068674e8683098bfa9ce8e10b2023-03-22T09:11:07ZengPensoft PublishersResearch Ideas and Outcomes2367-71632023-03-0191810.3897/rio.9.e101006101006pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian GeometryAnton Andreev0Grégoire Cattan1Sylvain Chevallier2Quentin Barthélemy3GIPSA-lab, CNRS, University of Grenoble-AlpesIBM SoftwareLISV, University of Paris-SaclayFoxteamQuantum computing is a promising technology for machine learning, in terms of computational costs and outcomes. In this work, we intend to provide a framework that facilitates the use of quantum machine learning in the domain of brain-computer interfaces – where biomedical signals, such as brain waves, are processed.To this end, we integrated Qiskit, a well-known quantum library, with pyRiemann, a framework for the analysis of biomedical signals using Riemannian Geometry. In this paper, we describe our approach, the main elements of our implementation and our research directions. A key result is the creation of a standardised pipeline (QuantumClassifierWithDefaultRiemannianPipeline) for the binary classification of brain waves. The git repository reported in this paper also contains a complete test suite and examples to guide practitioners. We believe that this software will enable further research on the joint field of brain-computer interfaces and quantum computing.https://riojournal.com/article/101006/download/pdf/information geometrymachine learningtime serie |
| spellingShingle | Anton Andreev Grégoire Cattan Sylvain Chevallier Quentin Barthélemy pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry Research Ideas and Outcomes information geometry machine learning time serie |
| title | pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry |
| title_full | pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry |
| title_fullStr | pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry |
| title_full_unstemmed | pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry |
| title_short | pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry |
| title_sort | pyriemann qiskit a sandbox for quantum classification experiments with riemannian geometry |
| topic | information geometry machine learning time serie |
| url | https://riojournal.com/article/101006/download/pdf/ |
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