Registration is now closed.
Please follow the talks live on the RIKEN-AIP YouTube channel.

Please note: The conference will be live streamed and the recorded videos will be available on the RIKEN-AIP YouTube channel

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
QTML 2021 is hosted by RIKEN-AIP (Center for Advanced Intelligence Project)
Important dates
  • Extended Abstract submission deadline: September 15
  • Poster deadline: October 8
  • Decision notification: October 15
  • (All dates 2021, 23:59 AoE)
Quick links Contact
  • Minh Ha Quang:
    minh.haquang-at-riken.jp