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Enhancing Machine Learning with Quantum Methods

Year: 2025

Type: conference-paper

Abstract: Quantum physics offers a new paradigm that promises to make certain computations faster and more efficient.The recent progress of quantum computers allows for more complex applications which lead to a rising interest in transferring machine learning methods to quantum hardware for practical applications.However, the development of quantum computers is still in its beginnings and currently these approaches require synergy with classical computers.We present some methods where this quantum-classical interplay is used to enhance machine learning approaches.

Source: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)

DOI: 10.14428/esann/2025.es2025-29

Authors: M. Lautaro Hickmann, Markus Lange, Hans-Martin Rieser

Institution: Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4409480263

FWCI:

Cites: 30

Cited by:

Related to: 10