Add to ORKGIn the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds at initialization. Qualitative arguments about the learning dynamics of the spatial pooler are then discussed
Memory for order information is studied by the presentation of a string of items, after which the su...
Most, if not all, visual input is hierarchically organised, consisting of both local and global leve...
Two experiments examined the effects of spatial and temporal contiguities in a working memory bindin...
In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activ...
In this study learning reinforcement and noise rejection of a spatial pooler was examined, the first...
Hierarchical temporal memory (HTM) is an emerging machine learning algorithm, with the potential to ...
Hierarchical temporal memory (HTM) provides a theoretical framework that models several key computat...
This article investigates hardware implementation of hierarchical temporal memory (HTM), a brain-ins...
Hierarchical Temporal Memory is a brain inspired memory prediction framework modeled after the unifo...
This study investigates whether memory for sequences of spatial locations can be represented hierarc...
Abstract — Hierarchical Temporal Memory (HTM) is still largely unknown by the pattern recognition co...
As a new type of artificial neural network model, HTM has become the focus of current research and a...
The progress in information technologies enables applications of artificial neural networks even in ...
Spatial learning involves the storage and replay of temporally ordered spatial information. The hip...
ii In an immediate serial recall task, participants are asked to recall lists of items in order. In ...
Memory for order information is studied by the presentation of a string of items, after which the su...
Most, if not all, visual input is hierarchically organised, consisting of both local and global leve...
Two experiments examined the effects of spatial and temporal contiguities in a working memory bindin...
In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activ...
In this study learning reinforcement and noise rejection of a spatial pooler was examined, the first...
Hierarchical temporal memory (HTM) is an emerging machine learning algorithm, with the potential to ...
Hierarchical temporal memory (HTM) provides a theoretical framework that models several key computat...
This article investigates hardware implementation of hierarchical temporal memory (HTM), a brain-ins...
Hierarchical Temporal Memory is a brain inspired memory prediction framework modeled after the unifo...
This study investigates whether memory for sequences of spatial locations can be represented hierarc...
Abstract — Hierarchical Temporal Memory (HTM) is still largely unknown by the pattern recognition co...
As a new type of artificial neural network model, HTM has become the focus of current research and a...
The progress in information technologies enables applications of artificial neural networks even in ...
Spatial learning involves the storage and replay of temporally ordered spatial information. The hip...
ii In an immediate serial recall task, participants are asked to recall lists of items in order. In ...
Memory for order information is studied by the presentation of a string of items, after which the su...
Most, if not all, visual input is hierarchically organised, consisting of both local and global leve...
Two experiments examined the effects of spatial and temporal contiguities in a working memory bindin...