Backend server for getting activation, neuron and explanation data via HTTP, either from Azure blob storage or from inference on a subject or assistant model. Gets activations, loss, or other ...

This repository experiments with best techniques to improve dense, volumetric semantic segmentation. Specifically, the model is of U-net architectural style and includes variational autoencoder (for ...

Abstract: Recently masked autoencoder (MAE) has achieved great success in visual representation learning and delivered promising potential in many downstream vision tasks. However, due to the lack of ...

Self-supervised learning approaches, such as masked autoencoder (MAE) reconstruction and contrastive learning, offer a promising solution by reducing reliance on labeled data. Nonetheless, Transformer ...

One of the advancements is from data scientist Paril Ghori, who has effectively used an Autoencoder deep learning model to identify anomalies in residential furnaces. Utilizing cutting-edge machine ...

It is aimed at creating, training, and deploying ML models. This course is aimed at those with a basic grasp of machine learning, Python, and deep learning. It helps you utilize and enhance those ...

Department of Statistics, University of Oxford, St Giles, Oxford OX1 3LB, U.K.