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Found 4 papers, 1 papers with code
Understanding Likelihood of Normalizing Flow and Image Complexity through the Lens of Out-of-Distribution Detection
Finally, we provide evidence of the potential applicability of our hypothesis in another DGM, PixelCNN++.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Frequency-aware GAN for Adversarial Manipulation Generation
We observe that existing spatial attacks cause large degradation in image quality and find the loss of high-frequency detailed components might be its major reason.
Out-of-Distribution Detection with Reconstruction Error and Typicality-based Penalty
The task of out-of-distribution (OOD) detection is vital to realize safe and reliable operation for real-world applications.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Regularization with Latent Space Virtual Adversarial Training
VAT utilizes adversarial samples, generated by injecting perturbation in the input space, for training and thereby enhances the generalization ability of a classifier.
