1 code implementation • 20 Nov 2022 • Vahid Reza Khazaie, Anthony Wong, Mohammad Sabokrou
This paper presents a novel evaluation framework for Out-of-Distribution (OOD) detection that aims to assess the performance of machine learning models in more realistic settings.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
no code implementations • 3 Jul 2022 • Vahid Reza Khazaie, Anthony Wong, John Taylor Jewell, Yalda Mohsenzadeh
The Adversarial Distorter is a convolutional encoder that learns to produce effective perturbations and the autoencoder is a deep convolutional neural network that aims to reconstruct the images from the perturbed latent feature space.
no code implementations • 3 Jul 2022 • Vahid Reza Khazaie, Anthony Wong, Yalda Mohsenzadeh
Therefore, training a regressor on these augmented samples will result in more separable distributions of labels for normal and real anomalous data points.