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Benoît Frénay

Towards a Trustworthy Anomaly Detection for Critical Applications through Approximated Partial AUC Loss

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Feb 17, 2025
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On the effectiveness of Rotation-Equivariance in U-Net: A Benchmark for Image Segmentation

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Dec 12, 2024
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SO and O Equivariance in Image Recognition with Bessel-Convolutional Neural Networks

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Apr 18, 2023
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Industrial and Medical Anomaly Detection Through Cycle-Consistent Adversarial Networks

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Feb 10, 2023
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Composite Score for Anomaly Detection in Imbalanced Real-World Industrial Dataset

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Nov 25, 2022
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DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality

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May 19, 2021
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Impact of Legal Requirements on Explainability in Machine Learning

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Jul 10, 2020
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Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning

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May 14, 2020
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