Quantum neural networks: a practical approach.

Cykl wykładów z informatyki kwantowej
January 20, 2020 6:00 PM

With recent success of artificial neural networks and emergence of Near Intermediate Scale Quantum computers a new field of quantum machine learning was established. There is hope that quantum computers will be able to build better and faster machine learning models. One of the quantum machine learning approaches is to embed quantum computers into neural network processing graphs. During the talk I will present the basic concepts of quantum neural networks, their training and application in multi-class supervised classification setting. I will show how to use two python libraries, namely: scikit learn and pennylane to perform training and inference using a particular type of a quantum neural network. Piotr Gawron (https://pgawron.github.io [1]) currently is the leader of the Scientific Computing & Information Technology Group and institute professor at AstroCeNT -- the Particle Astrophysics Science and Technology Centre International Research Agenda located in Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences. For eighteen years he was a member of the Quantum Systems of Informatics Group at the Institute of Theoretical and Applied Informatics of the Polish Academy Sciences in Gliwice. He graduated in computer science at the Silesian University of Technology, he obtained his doctoral degree in technical sciences at ITAI PAS and habilitated doctor degree at the faculty Automatic Control, Electronics and Computer Science at the Silesian University of Technology in Gliwice. He has been involved in quantum computer science research since his fourth year of study. In the past he was engaged in the research on quantum games, quantum walks, simulation of noisy quantum computers, quantum programming languages, quantum control, numerical shadows and tensor networks. Currently he is studying applicability of quantum machine learning for Earth observations imagery data processing, applications of quantum and classical machine learning techniques for gravitational wave and dark matter detection. The number of seats is limited, so please register as soon as possible (no later than 19.01, 23:59 CET) using the form: https://docs.google.com/forms/d/e/1FAIpQLSfXHI3YBGCctzi6UoFIsXJNrcTc_VnRdwi44CH_itDZsxw3UA/viewform You can find the details on the meeting's website: https://www.facebook.com/events/535006690419697 The meeting is organized in partnership with Centralny Dom Technologii and Daftcode - our strategic partner. We hope to see you soon!Warsaw Quantum Computing Group P.S.1 Let’s stay in touch on our Facebook group: https://www.facebook.com/groups/285214992075232 P.S.2 You can also join our mailing list at Google Groups: https://groups.google.com/forum/#!forum/warsaw-quantum-computing-group P.S.3 You can also follow our fanpage https://www.facebook.com/Warsaw-Quantum-Computing-Group-1936160966506139 and YouTube channel https://www.youtube.com/channel/UCoQAyPU5KQEpMOMDUN0j3IQ/videos Links: ------ [1] https://pgawron.github.io/.