On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

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In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

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On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

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