Journal Cover: Machine Learning Transfer Efficiencies for Noisy Quantum Walks
Our paper Machine Learning Transfer Efficiencies for Noisy Quantum Walks is now published in Advanced Quantum Technologies journal and is featured on the journal cover. Quantum walks is a tool for studying various phenomena in quantum systems, including quantum transport in complex networks. In article number 1900115, Alexey A. Melnikov and co‐workers suggest how to improve […]
Machine Learning Risk Institute Winter School
On 29-31 January 2020, I was lecturing about Reinforcement Learning at the multidisciplinary Machine Learning Winter School, University of Liverpool. There was a very interesting set of lectures on computer vision and important applications in healthcare, surveillance, and autonomous driving. http://riskinstitute.org.uk/events/machinelearning
Our new NJP publication: neural network separated quantum and classical effects in the space of networks
Predicting quantum advantage by quantum walk with convolutional neural networksAlexey A Melnikov et al 2019 New J. Phys. 21 125002https://doi.org/10.1088/1367-2630/ab5c5e
2019 Machine Learning for Quantum Technology Workshop
Workshop webiste:https://www.mpl.mpg.de/divisions/marquardt-division/workshops/2019-machine-learning-for-quantum-technology/ Videos of all talks:https://video.mpl.mpg.de/cat/mlqt-workshop My contributed talk:https://video.mpl.mpg.de/video/41/alexey-melnikov