In the "2nd Workshop on Machine Learning for Quantum Technology" we aim to attract researchers interested in the use of classical ML/AI techniques to advance the development of quantum technologies in a broad sense. Some examples would be analyzing quantum measurements, estimating the parameters of quantum devices, discovering new quantum experimental setups, protocols, and feedback strategies, and generally improving aspects of quantum computing, quantum communication, and quantum simulation. See the review paper here for more relevant topics. We will also cover some quantum machine learning topics and their interconnections with classical machine learning.
This meeting will consist of a first day of lectures/tutorials (November 5th), followed by a workshop from November 6th to November 8th. We will have invited talks, contributed talks and poster sessions. See the 1st edition of the workshop in 2019 here.
You can find the schedule here, and the book of abstracts here.
The list of confirmed invited speakers is available here.
The list of confirmed tutorials:
- Eliška Greplová (Delft University of Technology) - Condensed Matter Physics with Machine Learning
- Marin Bukov (MPI PKS) - Reinforcement Learning for Quantum Technologies
- Roger Melko (University of Waterloo & Perimeter Institute) - Autoregressive Models in Quantum Physics
Poster Printing
Grants
Unfortunately, we cannot provide any travel or accommodation grant to the participants.
Be aware - Scams
We have had reports of participants receiving emails claiming to offer accommodation for the conference. These are scam emails. If you are at all unsure about any communication you receive supposedly related to the conference, please do not give out any personal details. Contact the organizers via the contact email provided on the left panel to establish whether it is genuine or not. Official communications will be made only from that email.
