5 citations · 11 across the 3 of their papers we have counts for
3 papers
A deep convolutional neural network that is invariant to time rescaling
Brandon G. Jacques, Zoran Tiganj, Aakash Sarkar +2
Human learners can readily understand speech, or a melody, when it is presented slower or faster than usual. Although deep convolutional neural networks (CNNs) are extremely powerf…
DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales
Brandon Jacques, Zoran Tiganj, Marc W. Howard +1
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-wo…
Scale-invariant temporal history (SITH): optimal slicing of the past in an uncertain world
Tyler A. Spears, Brandon G. Jacques, Marc W. Howard +1
In both the human brain and any general artificial intelligence (AI), a representation of the past is necessary to predict the future. However, perfect storage of all experiences i…