Neural architecture search (NAS) is a branch of AutoML that attempts to find the best deep-learning model architecture ... this typically requires that each proposed model be fully trained on ...

Neural architecture ... models); learning curve extrapolation (based on a just a few epochs); warm-started training (initialize weights by copying them from a parent model); and one-shot models ...

Deep neural networks have gained fame for their capability to process visual information. And in the past few years, they have become a key component of many computer vision applications.

Become a Member The center’s faculty seeks active engagement toward building a robust, comprehensive, and scalable solution for an end-to-end deep learning training and model-serving architecture.

To address this issue, researchers at ETH Zurich have unveiled a revised version of the transformer, the deep ... architectural tweaks. These changes collectively maintain the model’s learning ...

This is the same model OpenAI uses for prediction, summarization, question answering, and more. This article explores the architecture ... form the cornerstone of deep learning technology.

Become a Member The center’s faculty seeks active engagement toward building a robust, comprehensive, and scalable solution for an end-to-end deep learning training and model-serving architecture.