Papers

1. On the Optimum Architecture of the Biologically Inspired Hierarchical Temporal Memory Model Applied to the Hand-Written Digit Recognition, 2010, Invited paper downloaded
2. MIT CSAIL report on Cortical Network Simulator(CNS), Feb 2010
3. Fixed Frame Temporal Pooling
4. GPGPU-BASED CORTICAL MODELING by Theodore Hilk, looks like a very good paper to read for Issue #6
5. Object class recognition and localization using sparse features with limited receptive fields, IJCV 2008
6. A survey on transfer learning, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 22, NO. 10, OCTOBER 2010
7. 715 citations of 'Survey on transfer learning'
8. Econophysics – complex correlations and trend switchings in financial time series, The European Physical Journal, 2011
   Not sure if there is any mention of HTM or other cortical models
9. Simple model of spiking neurons
10. Reservoir Computing Approaches to Recurrent Neural Network Training, [[http://dl.acm.org/citation.cfm?id=2296036|ACM link], Aug 2009
11. Google scholar 259 citations for above paper
12. Model Learning for Robot Control: A Survey - 2011, 31 citations in Google scholar
13. Ontology Learning from Text: A Look Back and into the Future, ACM Comput. Surveys, Aug 2012
14. Large-scale cortex simulation: methodology, tools & examples, 2009
15. Beyond streams & graphs: Dynamic Tensor Analysis (DTA), KDD06
    Cited by 190 other papers
16. Tensor analyzers, for face recognition
17. The Deep Tensor Neural Network With Applications to Large Vocabulary Speech Recognition, IEEE Trans. on Audio, speech & language processing, 2012
18. Discriminative Learning for Differing Training and Test Distributions, ICML 2007. ACM link has 49 citations
19. Google scholar has 149 citations for the above paper
20. A Literature Survey on Domain Adaptation of Statistical Classifiers, Mar 2008
21. Vhapter 3: Sparse Distributed Memory and Related Models, in M.H. Hassoun, ed., Associative Neural Memories: Theory and Implementation, pp. 50–76. New York: Oxford University Press, 1993.
22. Sparse Distributed Memory: Principles and Operation, Tech-Report, 1989
23. Kanerva's Sparse Distributed Memory: An Object-Oriented Implementation on the Connection Machine, IJCAI 1995
24. A New Training Algorithm for Kanerva’s Sparse Distributed Memory, Jul 2012
25. Sparse Distributed Memory for Experience-Based Robot Manipulation, 2009
26. Robot Navigation and Manipulation based on a Predictive Associative Memory, 2009, pdf link
27. Parallel implementation of a SDM using a GPU for vision-based robot navigation
28. Random Indexing of Text Samples for Latent Semantic Analysis
29. Sparse Distributed Memories in a Bounded Metric State Space: Some Theoretical and Empirical Results, Sep 2004
30. Hierarchical Temporal Memory Cortical Learning Algorithm for Pattern Recognition on Multi-core Architectures, by Ryan William Price, Portland State University, thesis, Jan 2011
31. A Study on Associative Neural Memories
32. Spatio-temporal memories for machine learning: a long-term memory organization, Mar 2009. PDF link], [[https:www.taoeffect.com/other/nupic/#fn12|referred from this blog entry by Greg Slepak
33. [[http://dl.acm.org/citation.cfm?id=2327980|Hierarchically Clustered Adaptive Quantization CMAC and Its Learning Convergence]. CMAC neural network (NN) is a well-established computational model of the human cerebellum.
34. Probabilistic Classification Vector Machines (PCVM)
35. TRAINING RECURRENT NEURAL NETWORKS
36. Comment: Boosting Algorithms: Regularization, Prediction and Model Fitting
37. Sparse ensemble learning for concept detection, Google citations - 8
38. Recent advances in efficient learning of recurrent networks, Google citations - 14
39. Temporal-Kernel Recurrent Neural Networks, Google citations - 5
40. A Comparative Study of Energy Minimization Methods for Markov Random Fields, Google cites - 274, Downloaded.

Collections & Special Issues

1. Spl. Issue on Learning Deep Architectures, IEEE Trans. on PAMI, Aug 2013
2. Neural Information Processing Series, MIT Press