Qhack 2022 Quantum Machine Learning

QHack 2022: Zoe Holmes —Expressibility & trainability: balancing the ingredients of an effective VQA

Zoe Holmes, Postdoctoral Fellow at Los Alamos National Lab, speaks at

Quantum Machine Learning: Opportunities and Challenges

Daniel Kyungdeock Park / Professor, Yonsei university.

Quantum Machine Learning | QuTech Academy

Video:

QHack 2021: Sofia Vallecorsa—Quantum Machine Learning in High Energy Physics: Examples from CERN

Sofia Vallecorsa, CERN Openlab AI and

Quantum Machine Learning Explained

... the exciting and highly active field of

QHack 2022: Marco Cerezo —Barren plateaus and overparametrization in quantum neural networks

Marco Cerezo, Staff Scientist at Los Alamos National Laboratory, speaks at

Quantum Machine Learning - Mária Kieferová - 3/6/2022

There is also some discrepancy between the interest of the

Quantum Machine Learning

A special lecture entitled "

QHack 2021: Amira Abbas—The Expressibility of Quantum Machine Learning Models

Amira Abbas, PhD candidate at University of KwaZulu-Natal and

QHack 2022: Jarrod McClean —Quantum advantage in learning from experiments & notes on dequantization

Jarrod McClean, Staff Research Scientist at Google

Amazon re:MARS 2022 - Quantum machine learning: Prospects and challenges (MLR337)

This session provides an overview of

Results with QuEra: new quantum machine learning results with quantum reservoir computing

Quantum

Marco Cerezo: Towards Geometric Quantum Machine Learning | QHack 2023

Marco Cerezo, Staff Scientist at Los Alamos National Laboratory, speaks at