Useful links

TensorFlow

• Tensorflow https://www.tensorflow.org/
• Examples of TensorFlow with multiple Machine Learning algorithms https://github.com/aymericdamien/TensorFlow-Examples
• Recurrent Neural Networks in TensorFlow http://r2rt.com/
• Deep Learning with Tensorflow Documentation http://deep-learning-tensorflow.readthedocs.io/en/latest/

Hopfield Networks

• Wikipedia Hopfield Network https://en.wikipedia.org/wiki/Hopfield_network
• Training based on the Hebbian Rule, introduced in http://s-f-walker.org.uk/pubsebooks/pdfs/The_Organization_of_Behavior-Donald_O._Hebb.pdf
• Hopfield implementation in numpy http://codeaffectionate.blogspot.com.es/2013/05/fun-with-hopfield-and-numpy.html
• Hopfield implementation with Storkey rule in Python https://www.doc.ic.ac.uk/project/2015/163/g1516322/#service
• Storkey Learning Rules for Hopfield Networks http://vixra.org/pdf/1309.0130v1.pdf
• The basins of attraction of a New Hopfield Learning Rule, Storkey, http://homepages.inf.ed.ac.uk/amos/publications/StorkeyValabregue1999TheBasinsofAttractionofaNewHopfieldLearningRule.pdf
• Neural networks and physical systems with emergent collective computational abilities, J. J. Hopfield, https://bi.snu.ac.kr/Courses/g-ai09-2/hopfield82.pdf

Restricted Boltzmann Machines

• Wikipedia Restricted Boltzmann machine https://en.wikipedia.org/wiki/Restricted_Boltzmann_machine
• Invention of RBMs under the name Harmonium (?) http://stanford.edu/~jlmcc/papers/PDP/Volume%201/Chap6_PDP86.pdf
• Theoretical introduction to RBMs http://image.diku.dk/igel/paper/TRBMAI.pdf <-- (algorithms, improvements)
• Practical guide to RBMs https://www.cs.toronto.edu/~hinton/absps/guideTR.pdf <-- (training, parameters)
• Another guide to RBMs https://deeplearning4j.org/restrictedboltzmannmachine
• Example of RBMs for image denoising:
• http://www.cs.toronto.edu/~tang/papers/robm.pdf
• https://arxiv.org/pdf/1301.3468.pdf
• Codes for RBMs:
• http://deeplearning.net/tutorial/rbm.html <-- (pos/neg phases, energy function)
• https://github.com/basavin/rbm-smple/blob/master/rbm.py
• Classification using Discriminative Restricted Boltzmann Machines http://machinelearning.org/archive/icml2008/papers/601.pdf

Boltzmann Machines

• Wikipedia Boltzmann Machine https://en.wikipedia.org/wiki/Boltzmann_machine
• A Learning Algorithm for Boltzmann Machines https://web.archive.org/web/20110718022336/http://learning.cs.toronto.edu/~hinton/absps/cogscibm.pdf

Interesting resources

• Definition of Autoassociative Memory https://en.wikipedia.org/wiki/Autoassociative_memory
• On the equivalence of Hopfield Networks and Boltzmann Machines https://arxiv.org/pdf/1105.2790v3.pdf