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Quantum Techniques in Machine Learning (QTML) is an annual international conference focusing on the interdisciplinary field of quantum technology and machine learning. The goal of the conference is to gather leading academic researchers and industry players to interact through a series of scientific talks focussed on the interplay between machine learning and quantum physics.

QTML was first hosted in Verona, Italy (2017), then in Durban, South Africa (2018),  Daejeon, South Korea (2019), virtual (2020, hosted by Zapata Computing), virtual (2021, hosted by RIKEN-AIP), and in Naples (2022). This seventh edition, QTML 2023, will be hosted by CERN, Switzerland.

Conference topics

Example topics include, but are not limited to:

Quantum algorithms for machine learning tasks

Learning and optimisation with hybrid quantum-classical methods

Tensor methods and quantum-inspired machine learning

Data encoding and processing in quantum systems

Machine learning for experimental quantum information

Quantum-enhanced robustness in machine-learning models

Quantum learning theory

Quantum variational circuits

Fuzzy logic for quantum machine learning

Quantum state reconstruction from data

Quantum tomography

Quantum algorithms for machine-learning tasks


Call for extended abstract & poster submissions

Deadline for abstract & poster submissions

Notification about abstract & poster acceptance

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QTML Conference