Closed KaterinaGratsea closed 2 years ago
Thank you @KaterinaGratsea! I will be reviewing it next week and I'll let you know when it's up in the page!
Perfect, thanks!
On Sat, Nov 20, 2021, 00:29 CatalinaAlbornoz @.***> wrote:
Thank you @KaterinaGratsea https://github.com/KaterinaGratsea! I will be reviewing it next week and I'll let you know when it's up in the page!
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Hi @KaterinaGratsea, congratulations on your Demo! It was very interesting to read and it ran without any errors. It should be up in the page by tomorrow so I'll let you know when it's there. This is really impressive work!
I will send you your Quantum Carnival ticket on a private message on Discord 😄 .
Thanks! Happy to hear that!
Looking forward to seeing it on the page.
Cheers,
Katerina
On Mon, Nov 22, 2021 at 8:13 PM CatalinaAlbornoz @.***> wrote:
Hi @KaterinaGratsea https://github.com/KaterinaGratsea, congratulations on your Demo! It was very interesting to read and it ran without any errors. It should be up in the page by tomorrow so I'll let you know when it's there. This is really impressive work!
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/PennyLaneAI/qml/issues/383#issuecomment-975792003, or unsubscribe https://github.com/notifications/unsubscribe-auth/AK5EWBPIINUWY24DMFX36K3UNKB4PANCNFSM5IM5KZOQ . Triage notifications on the go with GitHub Mobile for iOS https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675 or Android https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub.
Hi @KaterinaGratsea. The demo is up in the page! We will promote it in the next few days.
Thank you for this amazing contribution!
Now live, thanks for the submission @KaterinaGratsea!
General information
Name Katerina Gratsea and Patrick Huembeli
Affiliation (optional) Your affiliation, if applicable; e.g. University, research institute, company.
Twitter (optional) AGratsea and PHuembeli
Image (optional) https://drive.google.com/file/d/18o5UB3Mmb7x9HiF3C9su9m6YDLkNkLD8/view?usp=sharing
Demo information
Title Exploring quantum models with a teacher-student scheme.
Abstract Using PennyLane, we introduce a teacher-student scheme to systematically compare different QNN architectures and to evaluate their relative expressive power. This scheme avoids training with a specific dataset and compares the learning capacity of different quantum models.
Relevant links https://github.com/KaterinaGratsea/Teacher-student_scheme https://arxiv.org/abs/2105.01477