3 citations · 4 across the 2 of their papers we have counts for
3 papers · 1 filter
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…
Predicting the future with a scale-invariant temporal memory for the past
Wei Zhong Goh, Varun Ursekar, Marc W. Howard
In recent years it has become clear that the brain maintains a temporal memory of recent events stretching far into the past. This paper presents a neurally-inspired algorithm to u…