-
have dominated the field in recent years but often suffer from training instabilities. We aim to investigate the interactions between model architectures and data domains in deep learning, focusing
-
computations. Along with theoretical contribution to the field, there will be developed software to automatically optimize the training and inference of modern deep learning architectures. Potential applications
Searches related to architecture
Enter an email to receive alerts for architecture positions