Loosely speaking, deep learning is a branch of machine learning that uses multi-layer neural networks to build models for several tasks such as prediction or diagnosis. The unknown parameters, commonly referred to as weights, are estimated by minimizing a loss function often subject to some form of regularization. Deep learning has shown promise in many domains, with imaging based analysis being a common application area where deep learning models have shown promising performance. Several center members are working on deep learning related research including analyzing medical images, uncertainty quantification, and interpretability of deep learning models.
|Jon Steingrimsson||Fenghai Duan|