This study aims to explore an autoencoder-based method for generating brain MRI images of patients with Autism Spectrum Disorder (ASD) and non-ASD individuals, and to discriminate ASD based on the ...

Abstract: Class imbalance occurs in many real-world applications, including image classification, where the number of images in each class differs significantly. With imbalanced data, the generative ...

Which loss function did you use when training the autoencoder? Did you directly compute the MSE between the predicted SDF values and the ground truth? Additionally, how many steps did you train for?

A fairly common sub-problem in many machine learning and data science scenarios is the need to compute the similarity (or difference or distance) between two datasets. For example, if you select a ...

We propose Scenario Dreamer, a fully data-driven closed-loop generative simulator for autonomous vehicle planning. If you'd prefer to skip data extraction and preprocessing, you can directly download ...