Hierarchical Temporal Memory Concepts , Theory , and Terminology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep learning in neural networks: An overview (2014, background): “More recently,wellknown entrepreneurs (Hawkins & George, 2006; Kurzweil, 2012) also got interested in HTMs; compare also hierarchical HMMs (e.g., Fine, Singer, & Tishby, 1998), as well as later UL-based recurrent systems (Klampfl &Maass, 2013; Klapper-Rybicka et al., 2001; Steil, 2007; Young,…”
How the brain might work: a hierarchical and temporal model for learning and recognition (2008, methodology): “The theory of Hierarchical Temporal Memory, as expressed in [44] and further expanded in the previous chapters of this thesis, was developed by starting with the Memory-Prediction theory and by formalizing it using a mathematical framework.”
My First Deep Learning System of 1991 + Deep Learning Timeline 1962-2013 (2013, background): “Recently, well-known entrepreneurs also got interested [43, 52] in such hierarchical temporal memories [81, 82] (TL 1.7).”
AxNN: Energy-efficient neuromorphic systems using approximate computing (2014, background): “An important development within this field has been the advent of large-scale neural networks (NNs) such as Deep Learning Networks [1–3] (DLNs), Hierarchical Temporal Memory [4] (HTM), etc.”
Deep Learning of Invariant Spatio-Temporal Features from Video (2010, methodology): “We build feature invariance in a similar fashion to approaches such as Slow Feature Analysis [53] and Hierarchical Temporal Memory [16].”