Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection

Julia Wolleb; Florentin Bieder; Paul Friedrich; Peter Zhang; Alicia Durrer; Philippe C. Cattin

doi:10.1007/978-3-031-72120-5_13

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Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection

Julia Wolleb Florentin Bieder Paul Friedrich Peter Zhang Alicia Durrer Philippe C. Cattin

Year: 2024 Lecture notes in computer science Pages: 135-145 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-72120-5_13

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Keywords:

Computer science Bernoulli's principle Binary number Noise (video) Anomaly detection Diffusion Binary data Anomaly (physics) Artificial intelligence Pattern recognition (psychology) Speech recognition Mathematics Physics Arithmetic

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

COVID-19 diagnosis using AI

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Adversarial Robustness in Machine Learning

Physical Sciences → Computer Science → Artificial Intelligence

Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection

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