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 focused 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). This is the conference’s fifth annual year and will be held online (hosted by RIKEN).
Example topics include, but are not limited to
- Quantum algorithms for machine learning tasks
- Learning and optimization with hybrid quantum-classical methods
- Tensor methods and quantum-inspired machine learning
- Data encoding and processing in quantum systems
- Quantum learning theory
- Fuzzy logic for quantum machine learning
- Quantum state reconstruction from data
- Machine learning for experimental quantum information
- Quantum machine learning applications for industry