Software

Twitter FastText and Word2vec embeddings.

In my PhD thesis, I made a comparison between FastText and Word2vec word embeddings for PoS tagging and NER in Twitter microposts. You can find the embeddings on Github.

Contextual Decomposition for CNNs

As part of my paper, I have implemented a decomposition technique for convolutional neural networks. I allows you to understand which patterns the neural networks is looking for to make a certain decision. In my case, I was interested in comparing character-level patterns of CNNs and BiLSTMs. The implementation can be found here.

Twitter Word2vec model (WNUT Challenge)

As part of our ACL W-NUT 2015 shared task paper, we release a Twitter word2vec model trained on 400 million tweets, as described in detail in this paper. The code for this is currently not available but I recommend using the newer embeddings which you can find on Github.

Dynamic Convolutional Neural Networks

I have implemented the paper “A Convolutional Neural Network for Modelling Sentences” from Kalchbrenner et al. You can find the Theano implementation here.