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SUMMARY:Beyond Classical AI: Quantum Machine Learning for Anomaly Detection Across Industries
DESCRIPTION:Anomaly detection is one of the most critical challenges across industries\, from identifying equipment faults on a factory floor to flagging fraudulent transactions in financial services or detecting irregularities in medical diagnostics. But as data complexity grows and the cost of missed anomalies rises\, classical AI is beginning to show its limits. \nQuantum Machine Learning offers a fundamentally different approach. In collaboration with Fraunhofer ITWM\, WISER developed and benchmarked Quantum Neural Networks (QNNs) on real industrial data\, training models on sensor readings from pneumatic systems and rotating machinery to detect faults before they escalate. Our benchmark evaluates a range of encoding strategies and circuit configurations\, providing an assessment of the current practical performance of QML methods. \nThis session uses industrial defect detection as a test case\, but the core principles and model architectures apply directly to anomaly detection across many sectors\, including financial services (fraud and market surveillance)\, healthcare (diagnostic and drug quality issues)\, energy (grid faults and predictive maintenance)\, logistics (supply‑chain disruptions)\, and cybersecurity (network intrusions and threat patterns). \nIn this session\, you will: \n\n\n​See how WISER and Fraunhofer ITWM built QNN models for anomaly detection. \n\n\n​Understand how quantum circuit choices impact performance\, training\, and scalability. \n\n\n​Explore how QML anomaly detection compares to classical approaches. \n\n\n​Gain a clear view of where Quantum Machine Learning stands today and its path to adoption.
URL:https://www.qureca.com/calendar/beyond-classical-ai-quantum-machine-learning-for-anomaly-detection-across-industries/
CATEGORIES:Virtual
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DTSTART;TZID=UTC:20260714T140000
DTEND;TZID=UTC:20260714T170000
DTSTAMP:20260602T141942Z
CREATED:20260602T141942Z
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UID:10000498-1784037600-1784048400@www.qureca.com
SUMMARY:Quantum Safe Networks Forum
DESCRIPTION:How can the industry future-proof telecom Infrastructure against quantum threats? As quantum computing advances at breakneck speed\, the telecom industry faces an urgent challenge: safeguarding networks against the looming threat of quantum-enabled cyberattacks.  \nThe Quantum-Safe Networks Forum brings together telecom operators\, cybersecurity experts\, and industry analysts to explore how to build resilient\, future-ready infrastructure in the face of quantum disruption.
URL:https://www.qureca.com/calendar/quantum-safe-networks-forum/
CATEGORIES:Virtual
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20260826
DTEND;VALUE=DATE:20260827
DTSTAMP:20260819T232600Z
CREATED:20260819T232600Z
LAST-MODIFIED:20260819T232600Z
UID:10000511-1787702400-1787788799@www.qureca.com
SUMMARY:Quantum Error Correction/Detection and Dynamical Decoupling: Better Together or Apart?
DESCRIPTION:Join Quantum Machines for an insightful seminar exploring the relationship between quantum error correction/detection (QEC/QED) and dynamical decoupling (DD). \nThe session will explore how these two approaches can work together to reduce errors and improve the reliability and performance of quantum computing systems. It will also introduce a theoretical framework for understanding when combining QEC and DD can provide meaningful advantages. \nLed by Prof. Daniel Lidar\, the seminar will connect theory with experimental results from superconducting quantum processors. \nWhether you work in quantum research\, develop quantum technologies\, or are simply interested in the future of fault-tolerant quantum computing\, this session offers a valuable opportunity to learn about current approaches to tackling quantum errors.
URL:https://www.qureca.com/calendar/quantum-error-correction-detection-and-dynamical-decoupling-better-together-or-apart/
CATEGORIES:Virtual
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