Pragmatic Deep Learning

Some of the contemporary limitations of deep learning can be traced back to the fields early days. At Auton Lab, we try to unlock the same benefits of deep learning with novel approaches that reduce the complexity or the appetite for data. Additionally, a goal is to increase interpretability by keeping models as simple. This thrust involves building new model classes that are capable of deep learning while possessing structural advantages that make the methods applicable in select real-world contexts.