Per B Sederberg

DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales

Extracting temporal relationships over a range of scales is a hallmark of human perception and cognition---and thus it is a critical feature of machine learning applied to real-world problems. Neural networks are either plagued by the exploding/vanishing gradient problem in recurrent neural network…