# CRF([Conditional Random Fields](http://blog.echen.me/2012/01/03/introduction-to-conditional-random-fields/))

## Repos

* https://github.com/kmkurn/pytorch-crf
* https://github.com/allenai/allennlp
* https://github.com/mtreviso/linear-chain-crf

## Reference

* [Overview of Conditional Random Fields](https://medium.com/ml2vec/overview-of-conditional-random-fields-68a2a20fa541)
* [Introduction to Conditional Random Fields](http://blog.echen.me/2012/01/03/introduction-to-conditional-random-fields/)]
* [Viterbi algorithm](https://en.wikipedia.org/wiki/Viterbi_algorithm)
* [Conditional Random Field Tutorial in PyTorch](https://towardsdatascience.com/conditional-random-field-tutorial-in-pytorch-ca0d04499463)
* [Implementing a linear-chain Conditional Random Field (CRF) in PyTorch](https://towardsdatascience.com/implementing-a-linear-chain-conditional-random-field-crf-in-pytorch-16b0b9c4b4ea)

* .https://homepages.inf.ed.ac.uk/csutton/publications/crftutv2.pdf
* [Implementing a linear-chain Conditional Random Field (CRF) in PyTorch](https://towardsdatascience.com/implementing-a-linear-chain-conditional-random-field-crf-in-pytorch-16b0b9c4b4ea)



* http://www.cs.columbia.edu/~mcollins/

* [Tagging Problems, and Hidden Markov Models](http://www.cs.columbia.edu/~mcollins/hmms-spring2013.pdf)
* http://www.cs.columbia.edu/~mcollins/crf.pdf
* [The Forward-Backward Algorithm](http://www.cs.columbia.edu/~mcollins/fb.pdf)

* [The Naive Bayes Model, Maximum-Likelihood Estimation, and the EM Algorithm](http://www.cs.columbia.edu/~mcollins/em.pdf)

