Merge branch 'master' into dev

_static/authors/kilian_tscharke.txt

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+.. bio:: Kilian Tscharke
+ :photo: ../_static/authors/kilian_tscharke.jpg
+
+ Kilian Tscharke is a researcher at Fraunhofer AISEC and PhD student at Technical University Munich (TUM). His research interests lie at the intersection of quantum computing, machine learning and IT security.

_static/authors/maxi_wendlinger.txt

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+.. bio:: Maxi Wendlinger
+ :photo: ../_static/authors/maxi_wendlinger.jpg
+
+ Maxi Wendlinger is a researcher at Fraunhofer AISEC interested in the applications of cybersecurity in the era of Artificial Intelligence and Quantum Computing. He is currently pursuing his M.Sc. in Informatics at Technical University of Munich (TUM) with focus on Deep Learning and Quantum Computing.

demonstrations/tutorial_adversarial_attacks_QML.metadata.json

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+{
+ "title": "Adversarial attacks and robustness for quantum machine learning",
+ "authors": [
+ {
+ "username": "mxw"
+ },
+ {
+ "username": "kil"
+
+ }
+ ],
+ "dateOfPublication": "2024-09-16T00:00:00+00:00",
+ "dateOfLastModification": "2024-09-16T00:00:00+00:00",
+ "categories": ["Quantum Machine Learning", "Quantum Computing"],
+ "tags": ["Quantum machine learning", "QML", "Adversarial attacks", "Quantum security"],
+ "previewImages": [
+ {
+ "type": "thumbnail",
+ "uri": "/_static/demo_thumbnails/regular_demo_thumbnails/thumbnail_adversarial_attacks_qml.png"
+ },
+ {
+ "type": "large_thumbnail",
+ "uri": "/_static/demo_thumbnails/large_demo_thumbnails/thumbnail_large_adversarial_attacks_qml.png"
+ }
+ ],
+ "seoDescription": "Learn how to construct adversarial attacks on classification networks and how to make quantum machine learning (QML) models more robust.",
+ "doi": "",
+ "canonicalURL": "/qml/demos/tutorial_adversarial_attacks_QML",
+ "references": [
+ {
+ "id": "Wendlinger2024",
+ "type": "preprint",
+ "title": "A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models",
+ "authors": "Maximilian Wendlinger, Kilian Tscharke, Pascal Debus",
+ "year": "2024",
+ "doi": "10.48550/arXiv.2404.16154",
+ "url": "https://arxiv.org/abs/2404.16154"
+ },
+ {
+ "id": "Goodfellow2014",
+ "type": "preprint",
+ "title": "Explaining and harnessing adversarial examples",
+ "authors": "Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy",
+ "year": "2014",
+ "doi": "10.48550/arXiv.1412.6572",
+ "url": "https://arxiv.org/abs/1412.6572"
+
+ },
+ {
+ "id": "Liu2020",
+ "type": "preprint",
+ "title": "A rigorous and robust quantum speed-up in supervised machine learning",
+ "authors": "Yunchao Liu, Srinivasan Arunachalam, Kristan Temme",
+ "year": "2020",
+ "doi": "10.48550/arXiv.2010.02174",
+ "url": "https://arxiv.org/abs/2010.02174"
+
+ },
+ {
+ "id": "Lu2019",
+ "type": "preprint",
+ "title": "Quantum Adversarial Machine Learning",
+ "authors": "Sirui Lu, Lu-Ming Duan, Dong-Ling Deng",
+ "year": "2019",
+ "doi": "10.48550/arXiv.2001.00030",
+ "url": "https://arxiv.org/abs/2001.00030"
+
+ }
+ ],
+ "basedOnPapers": ["10.48550/arXiv.2404.16154"],
+ "referencedByPapers": [],
+ "relatedContent": [
+ {
+ "type": "demonstration",
+ "id": "tutorial_variational_classifier",
+ "weight": 1.0
+ }
+ ],
+ "hardware": []
+}