Speaker
Lourens van Niekerk
(Forschungszentrum Jülich)
Description
Anomaly detection (AD) is useful in medical assessment, fraud
detection, earth observation, and many more areas. These applications usually rely on deep time-series (TS) data,
in which anomalies could be complex and difficult to detect. Autoencoders have proven effective at TSAD, yet a systematic,
rigorous benchmark of quantum autoencoders is lacking. We are conducting a comprehensive study for these purposes,
and comparing against state-of-the-art classical models.
| Topic | Quantum variational circuits and their applications |
|---|---|
| Additional Topic | Machine learning techniques for experimental quantum information science |
Author
Lourens van Niekerk
(Forschungszentrum Jülich)
Co-authors
Dr
Dennis Willsch
(Forschungszentrum Jülich)
Prof.
Kristel Michielsen
(Forschungszentrum Jülich)